An electromagnetic force compensation method and system based on virtual displacement

Abstract

The application provides an electromagnetic force compensation method and system based on virtual displacement, relates to the technical field of electromagnetic force compensation, constructs an electromagnetic regulation and control system, calculates first electromagnetic force compensation data and second electromagnetic force compensation data, obtains a compensation amount ratio and a corresponding compensation amount gradient, analyzes dynamic items and constraint conditions respectively, triggers a dynamic item gradient corresponding instruction and / or a constraint gradient corresponding instruction according to analysis information, further obtains a dynamic item influence ratio and / or a constraint condition influence ratio, determines a compensation amount influence factor through the compensation amount gradient data, the dynamic item influence ratio and / or the constraint condition influence ratio, and further adjusts influence data, so that the electromagnetic force compensation can be classified and adjusted when the electromagnetic force influence factor changes, and the accuracy of the electromagnetic force compensation is improved.

Description

TECHNICAL FIELD

[0001] The application provides an electromagnetic force compensation method and system based on virtual displacement, and relates to the technical field of electromagnetic force compensation, in particular to the technical field of electromagnetic force compensation based on virtual displacement. BACKGROUND

[0002] With the evolution of systems to high speed, high load, and strong disturbance environment, the traditional electromagnetic force regulation technology faces two major influencing factors of dynamic term influence and constraint boundary conflict, and the prior art mainly responds to the above problems through fixed gain compensation or discrete constraint management, but has defects such as contradiction between compensation accuracy and robustness, constraint priority conflict, and difficulty in determining the influencing factor category. SUMMARY

[0003] The application provides an electromagnetic force compensation method and system based on virtual displacement to solve the above problems.

[0004] The application provides an electromagnetic force compensation method and system based on virtual displacement, and the method comprises the following steps:

[0005] S1, constructing an electromagnetic regulation system, obtaining an initial electromagnetic force, and calculating first electromagnetic force compensation data;

[0006] S2, monitoring the change data of the initial electromagnetic force, calculating second electromagnetic force compensation data according to the change data, and obtaining the compensation ratio and the corresponding compensation gradient according to the second electromagnetic force compensation data and the first electromagnetic force compensation data;

[0007] S3, analyzing the dynamic term and the constraint condition respectively, triggering the dynamic term gradient corresponding instruction and / or the constraint gradient corresponding instruction according to the analysis information, and then obtaining the dynamic term influence ratio and / or the constraint condition influence ratio;

[0008] S4, determining the compensation influence factor through the compensation gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio, and then adjusting the influence data.

[0009] Further, the S1 comprises:

[0010] The electromagnetic regulation system is constructed by an electromagnetic output system and an electromagnetic receiving system;

[0011] The initial electromagnetic force of the electromagnetic regulation system is obtained, the initial virtual work is calculated through the initial electromagnetic force, the system balance state is determined through the initial virtual work, and the system balance state determination information is obtained;

[0012] The electromagnetic compensation amount is obtained according to the system balance state determination information, and the target virtual work is obtained according to the electromagnetic compensation amount;

[0013] According to the target virtual work, the system balance state of the electromagnetic regulation system is determined again, and the system balance state determination information is balanced state.

[0014] When the system balance state determination information is balanced state, the current compensation quantity is calculated according to the electromagnetic compensation quantity and the Jacobian matrix, the current is adjusted through the current compensation quantity, and then the electromagnetic force compensation is carried out, and the first electromagnetic force compensation data is obtained.

[0015] Further, the S2 comprises:

[0016] The initial electromagnetic force is continuously monitored to obtain electromagnetic force change data.

[0017] The electromagnetic force change data is subjected to change state determination to obtain electromagnetic force state determination information.

[0018] Second electromagnetic force compensation data is obtained according to the electromagnetic force state determination information.

[0019] The ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data is calculated to obtain a compensation quantity ratio.

[0020] A preset compensation quantity ratio gradient is obtained, and the compensation quantity ratio is compared with the preset compensation quantity difference gradient to obtain a corresponding compensation quantity gradient of the compensation quantity ratio.

[0021] Further, the S3 comprises:

[0022] The dynamic term is continuously monitored to obtain dynamic term change data.

[0023] The dynamic term change data is subjected to change state determination to obtain dynamic term state determination information.

[0024] The dynamic term gradient corresponding instruction is triggered according to the dynamic term state determination information.

[0025] The dynamic term data when the dynamic term gradient corresponding instruction is triggered is obtained to obtain dynamic term influence data.

[0026] The dynamic term influence ratio is calculated through the dynamic term influence data.

[0027] The constraint condition data is continuously monitored to obtain constraint condition change data.

[0028] The constraint condition change data is subjected to change state determination to obtain constraint condition state determination information.

[0029] The constraint gradient corresponding instruction is triggered according to the constraint condition state determination information.

[0030] The constraint condition data when the constraint gradient corresponding instruction is triggered is obtained to obtain constraint condition influence data.

[0031] The constraint condition influence data, such as a constraint condition influence ratio, is calculated.

[0032] Further, the S4 comprises:

[0033] When the dynamic term gradient corresponding instruction and the constraint gradient corresponding instruction are acquired, the compensation influence factor is determined by the compensation gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio; when the compensation influence factor is the dynamic term, the electromagnetic force compensation data is recalculated and adjusted to obtain electromagnetic force compensation adjustment data.

[0034] When the compensation influence factor is the constraint condition, the constraint condition is adjusted to obtain constraint condition adjustment data.

[0035] Further, the system comprises:

[0036] The first compensation calculation module is configured to construct an electromagnetic regulation system, acquire an initial electromagnetic force, and calculate first electromagnetic force compensation data.

[0037] The comparative compensation analysis module is configured to monitor change data of the initial electromagnetic force, calculate second electromagnetic force compensation data according to the change data, and acquire a compensation ratio and a corresponding compensation gradient of the compensation ratio according to the second electromagnetic force compensation data in combination with the first electromagnetic force compensation data.

[0038] The influence factor analysis module is configured to analyze the dynamic term and the constraint condition respectively, trigger a dynamic term gradient corresponding instruction and / or a constraint gradient corresponding instruction according to analysis information, and further acquire a dynamic term influence ratio and / or a constraint condition influence ratio.

[0039] The factor determination and adjustment module is configured to determine a compensation influence factor by the compensation gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio, and further adjust the influence data.

[0040] Further, the first compensation calculation module comprises:

[0041] The system construction module is configured to construct an electromagnetic regulation system by an electromagnetic output system and an electromagnetic receiving system.

[0042] The preliminary determination module is configured to acquire an initial electromagnetic force of the electromagnetic regulation system, calculate an initial virtual work by the initial electromagnetic force, determine a system balance state of the electromagnetic regulation system by the initial virtual work, and obtain system balance state determination information.

[0043] The depth determination module is configured to acquire an electromagnetic compensation amount according to the system balance state determination information, and acquire a target virtual work according to the electromagnetic compensation amount.

[0044] According to the target virtual power, the electromagnetic regulation system is balanced again, and the system balance state is determined until the system balance state determination information is balanced.

[0045] The preliminary acquisition module is configured to, when the system balance state determination information is balanced, calculate a current compensation amount according to the electromagnetic compensation amount and a Jacobian matrix, adjust the current through the current compensation amount, and then compensate the electromagnetic force to obtain first electromagnetic force compensation data.

[0046] Further, the comparative compensation analysis module comprises:

[0047] The second acquisition module is configured to continuously monitor the initial electromagnetic force to obtain electromagnetic force change data.

[0048] The electromagnetic force change data is subjected to change state determination to obtain electromagnetic force state determination information.

[0049] The second electromagnetic force compensation data is obtained according to the electromagnetic force state determination information.

[0050] The comparative gradient corresponding module is configured to calculate a ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data to obtain a compensation amount ratio.

[0051] A preset compensation amount ratio gradient is obtained, and the compensation amount ratio is compared with the preset compensation amount difference gradient to obtain a corresponding compensation amount gradient of the compensation amount ratio.

[0052] Further, the influence factor analysis module comprises:

[0053] The dynamic term analysis module is configured to continuously monitor the dynamic term to obtain dynamic term change data.

[0054] The dynamic term change data is subjected to change state determination to obtain dynamic term state determination information.

[0055] The dynamic term gradient corresponding instruction is triggered according to the dynamic term state determination information.

[0056] The dynamic term data when the dynamic term gradient corresponding instruction is triggered is obtained to obtain dynamic term influence data.

[0057] The dynamic term influence ratio is calculated through the dynamic term influence data.

[0058] The constraint condition analysis module is configured to continuously monitor the constraint condition data to obtain constraint condition change data.

[0059] The constraint condition change data is subjected to change state determination to obtain constraint condition state determination information.

[0060] The constraint gradient corresponding instruction is triggered according to the constraint condition state determination information.

[0061] obtain constraint condition influence data when the constraint condition data corresponding to the constraint gradient trigger instruction is acquired;

[0062] calculate the constraint condition influence ratio through the constraint condition influence data.

[0063] Further, the factor determination adjustment module comprises:

[0064] The influence factor determination module is configured to, when the dynamic item gradient corresponding instruction and the constraint gradient corresponding instruction are acquired, determine the compensation influence factor through the compensation gradient data, the dynamic item influence ratio and / or the constraint condition influence ratio.

[0065] The factor adjustment module is configured to, when the compensation influence factor is the dynamic item, recalculate and adjust the electromagnetic force compensation data to obtain the electromagnetic force compensation adjustment data.

[0066] When the compensation influence factor is the constraint condition, the constraint condition is adjusted to obtain the constraint condition adjustment data.

[0067] The present application has the following advantages: The electromagnetic force compensation is adjusted according to the analysis data, and the system always meets the dynamic demand and the constraint condition. The compensation gradient is calculated by continuously monitoring the electromagnetic force change data, and the compensation amount can be adjusted in real time, which effectively offsets the dynamic interference (such as load mutation and external vibration), and improves the dynamic response speed of the system. The compensation gradient mechanism avoids the mutation of the compensation amount, and ensures the smooth operation of the system. The constraint gradient instruction is triggered by monitoring the constraint condition change data, and the system always operates within the safety boundary. When the dynamic item and the constraint condition conflict (such as the inertia force demand compensation amount exceeding the constraint upper limit), the influence ratio is analyzed to preferentially meet the key constraint. At the same time, the influence of the dynamic item and the constraint condition is considered, and the system instability caused by single factor compensation (such as overcompensation caused by only compensating the inertia force and ignoring the constraint condition) is avoided.

[0068] The compensation demand is predicted in advance through the virtual displacement principle, and the adaptability of the system to complex working conditions (such as nonlinear load and time-varying disturbance) is enhanced. The compensation amount is adjusted according to the actual demand, and energy waste caused by overcompensation is avoided. Under the premise of meeting the constraint condition, the compensation strategy is dynamically adjusted to reduce energy consumption. BRIEF DESCRIPTION OF DRAWINGS

[0069] Figure 1 It is a schematic diagram of an electromagnetic force compensation method based on virtual displacement. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0071] One embodiment of the present application, the present application proposes a virtual displacement-based electromagnetic force compensation method and system, the method comprises:

[0072] S1, constructing an electromagnetic control system, obtaining an initial electromagnetic force, calculating first electromagnetic force compensation data;

[0073] S2, monitoring the change data of the initial electromagnetic force, calculating the second electromagnetic force compensation data according to the change data, and obtaining the compensation ratio and its corresponding compensation gradient according to the second electromagnetic force compensation data combined with the first electromagnetic force compensation data;

[0074] S3, respectively analyzing the dynamic term and the constraint condition, triggering the dynamic term gradient corresponding instruction and / or the constraint gradient corresponding instruction according to the analysis information, and then obtaining the dynamic term influence ratio and / or the constraint condition influence ratio;

[0075] S4, determining the compensation influence factor through the compensation gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio, and then adjusting the influence data, such as Figure 1 as shown.

[0076] The working principle and technical effects of the above technical solution are: constructing an electromagnetic control system, interacting with the target object (such as a suspended body, a driving platform) through an electromagnetic field to generate an initial electromagnetic force. According to the initial state electromagnetic data of the target object, the first electromagnetic force compensation data is calculated to offset the initial lack of electromagnetic force.

[0077] The change data of the initial electromagnetic force is continuously monitored by the force sensor, and the second electromagnetic force compensation data is calculated according to the monitored electromagnetic force change data. The second compensation data reflects the dynamic demand of the electromagnetic force in the system running process (such as load change, external disturbance).

[0078] The ratio of the second compensation data to the first compensation data is calculated to obtain the compensation gradient.

[0079] The dynamic term (such as inertia force, damping force) affecting the electromagnetic force is analyzed, and the dynamic term influence ratio is calculated.

[0080] The system running boundary is analyzed to obtain the constraint condition change data, and the constraint condition influence ratio is calculated.

[0081] According to the dynamic term analysis result, the dynamic term gradient corresponding instruction is triggered.

[0082] According to the constraint condition analysis result, the constraint gradient corresponding instruction is triggered.

[0083] The compensation gradient data, the dynamic term influence ratio and the constraint condition influence ratio are analyzed to determine the main factors affecting the electromagnetic force compensation.

[0084] If the dynamic term has a dominant effect, prioritize adjusting the dynamic term compensation strategy.

[0085] If the constraint condition has a significant impact, prioritize adjusting the compensation strategy corresponding to the constraint condition (such as reducing the upper limit of the compensation amount).

[0086] According to the analysis results, adjust the electromagnetic force compensation amount to ensure that the system always meets the dynamic demand and constraint condition.

[0087] By continuously monitoring the electromagnetic force change data and calculating the compensation amount gradient, the compensation amount can be adjusted in real time to effectively offset dynamic disturbances (such as load sudden changes and external vibrations), improving the system's dynamic response speed.

[0088] The compensation amount gradient mechanism avoids sudden changes in the compensation amount, ensuring smooth system operation.

[0089] By monitoring the constraint condition change data and triggering the constraint gradient instruction, the system can always operate within the safety boundary.

[0090] When the dynamic term and the constraint condition conflict (such as the inertia force demand compensation amount exceeding the constraint upper limit), prioritize meeting the key constraints through impact ratio analysis.

[0091] By considering the effects of both dynamic terms and constraint conditions, the system instability caused by single-factor compensation (such as overcompensation caused by only compensating for inertia force while ignoring constraint conditions) is avoided.

[0092] By using the virtual displacement principle to predict compensation demand in advance, the system's adaptability to complex working conditions (such as nonlinear loads and time-varying disturbances) is enhanced.

[0093] Adjust the compensation amount according to actual demand to avoid energy waste caused by overcompensation.

[0094] Under the premise of meeting the constraint condition, dynamically adjust the compensation strategy to reduce energy consumption.

[0095] In one embodiment of the present application, the S1 includes:

[0096] An electromagnetic control system is constructed by an electromagnetic output system and an electromagnetic receiving system;

[0097] An initial electromagnetic force of the electromagnetic control system is obtained, an initial virtual work is calculated through the initial electromagnetic force, a system balance state determination of the electromagnetic control system is performed through the initial virtual work, and system balance state determination information is obtained;

[0098] An electromagnetic compensation amount is obtained according to the system balance state determination information, and a target virtual work is obtained according to the electromagnetic compensation amount;

[0099] The system balance state determination of the electromagnetic control system is performed again according to the target virtual work until the system balance determination information is in a balanced state.

[0100] When the system balance state determination information is a balanced state, the electromagnetic compensation amount is calculated according to the Jacobian matrix and the current compensation amount, the current is adjusted through the current compensation amount, and then the electromagnetic force compensation is performed to obtain first electromagnetic force compensation data.

[0101] The working principle and technical effects of the above technical solution are: an electromagnetic regulation and control system is constructed by an electromagnetic output system and an electromagnetic receiving system; the electromagnetic output system is a device for achieving the purpose of electromagnetic regulation and control of output current, and the electromagnetic receiving system is a device for passively performing electromagnetic force compensation.

[0102] The specific steps of the above method include:

[0103] An initial virtual work is obtained, and a calculation formula of the initial virtual work is:

[0104] delta W 01 =F0*delta Z

[0105] Wherein, delta W 01 is the initial virtual work, F0 is the initial electromagnetic force, and delta Z is an infinitesimal displacement (virtual displacement) of imagination.

[0106] When F0 is insufficient to balance the load, a virtual displacement is generated, and F0*delta Z is negative at this time, and the system is unstable.

[0107] The suction force Delta F is increased by increasing the current Delta I, and the target virtual work is obtained through Delta F.

[0108] The calculation method of the Delta F includes:

[0109] First, the Jacobian matrix is calculated.

[0110]

[0111] Wherein, J is the Jacobian matrix, is the partial derivative of the electromagnetic force to the displacement.

[0112] The electromagnetic compensation amount is calculated through the Jacobian matrix and the virtual displacement:

[0113] Delta F=J*delta Z

[0114] Wherein, Delta F is the electromagnetic compensation amount, and J is the Jacobian matrix.

[0115] The calculation formula of the target virtual work is:

[0116] The virtual work delta W=(F0+Delta F)*delta Z=0 (balanced state).

[0117] delta W 02 =(F0+Delta F)*delta Z

[0118] At this time (F0+ΔF)*δZ=0, the system is in equilibrium state.

[0119] The current compensation amount is calculated by combining the electromagnetic compensation amount with the Jacobian matrix.

[0120] The formula for calculating the current compensation amount is:

[0121]

[0122] Where ΔI is the current compensation amount.

[0123] The initial electromagnetic force of the system is obtained through sensors (such as force sensors, Hall effect sensors) in the electromagnetic control system. The initial electromagnetic force reflects the electromagnetic action intensity of the system in the initial state. Based on the virtual displacement principle, the initial virtual work is calculated by the product of the initial electromagnetic force and the virtual displacement. The virtual displacement is the small displacement allowed by the system under the constraint condition, and the virtual work reflects the energy change trend of the system under this displacement. The system equilibrium state judgment information (such as "unbalanced" or "balanced") is generated.

[0124] According to the system equilibrium state judgment information, the electromagnetic compensation amount is calculated. The electromagnetic compensation amount is used to offset the unbalanced force in the system (such as increasing or decreasing the electromagnetic force).

[0125] Based on the product of the electromagnetic compensation amount and the virtual displacement, the target virtual work is calculated. The target virtual work reflects the energy change trend of the system after compensation, and needs to meet the balance condition.

[0126] When the system reaches the equilibrium state, the current compensation amount is calculated according to the electromagnetic compensation amount combined with the Jacobian matrix (a linearized model describing the relationship between electromagnetic force and current). The Jacobian matrix reflects the sensitivity of electromagnetic force to current.

[0127] The current compensation amount is used to adjust the current in the electromagnetic control system (such as increasing or decreasing the driving current of the electromagnet), thereby realizing accurate compensation of the electromagnetic force and obtaining the first electromagnetic force compensation data.

[0128] Through virtual work calculation and balance judgment, accurate judgment of the system equilibrium state is realized. The virtual work is zero, which is a sufficient and necessary condition for the system to be in equilibrium, ensuring the accuracy of the judgment result.

[0129] Through iterative calculation of the target virtual work and adjustment of the electromagnetic compensation amount, the real equilibrium state of the system is gradually approached, avoiding the local optimal problem that may exist in the traditional method.

[0130] The electromagnetic compensation amount is converted into the current compensation amount through the Jacobian matrix, realizing accurate control of the electromagnetic force compensation. The linearization of the Jacobian matrix simplifies the control difficulty of the complex nonlinear system.

[0131] During system operation, the electromagnetic force change can be monitored in real time, and the current compensation amount can be dynamically adjusted to ensure that the electromagnetic force always meets the balance requirement.

[0132] Through the virtual work balance determination and the closed-loop control of the electromagnetic force compensation, the system can automatically adjust to the balance state, and effectively suppress the influence of external interference on the system.

[0133] Under dynamic working conditions, the system can quickly respond and adjust the electromagnetic force compensation amount to maintain stable operation.

[0134] In one embodiment of the present application, the S2 comprises:

[0135] The initial electromagnetic force is continuously monitored to obtain electromagnetic force change data.

[0136] The electromagnetic force change data is subjected to change state determination to obtain electromagnetic force state determination information.

[0137] Second electromagnetic force compensation data is obtained according to the electromagnetic force state determination information.

[0138] The ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data is calculated to obtain a compensation amount ratio.

[0139] A preset compensation amount ratio gradient is obtained, and the compensation amount ratio is compared with the preset compensation amount difference gradient to obtain a corresponding compensation amount gradient of the compensation amount ratio. The compensation amount gradient reflects the influence factor coefficient (the influence factors include dynamic terms and / or constraint conditions, etc.).

[0140] The working principle and technical effects of the above technical solution are as follows: the initial electromagnetic force in the electromagnetic regulation and control system is monitored in real time to obtain a continuous data stream of the electromagnetic force change over time.

[0141] The monitoring data is subjected to filtering (such as Kalman filtering, sliding average filtering) and noise reduction processing to eliminate noise interference and retain the true trend of the electromagnetic force change.

[0142] The state is determined according to the characteristics of the electromagnetic force change data.

[0143] When the change characteristic is greater than a preset change threshold (which can be set according to experience or industry standards), the second electromagnetic force compensation data is calculated according to the above electromagnetic force compensation data calculation steps. The compensation data reflects the deviation of the current electromagnetic force requirement from the initial state.

[0144] The ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data (i.e. the compensation amount ratio) is calculated.

[0145] The preset compensation amount ratio gradient (such as "slow gradient", "fast gradient", "over-limit gradient") corresponds to different ratio determination ranges. For example:

[0146] Slow gradient: ratio < 10% / s;

[0147] Fast gradient: ratio 10%-50% / s;

[0148] Excessive gradient: ratio > 50% / s.

[0149] Compare the compensation ratio with preset gradients to determine the compensation gradient corresponding to the current compensation ratio. For example:

[0150] If the ratio is 30%, it is determined to be a "fast gradient".

[0151] The compensation gradient reflects the speed of change in electromagnetic force demand, and indirectly reflects the category and strength of the influencing factors (such as dynamic terms and constraint conditions). For example:

[0152] A fast gradient may be caused by a sudden change in inertial force or a sudden change in constraint condition (data exceeding the extreme value);

[0153] An excessive gradient may trigger a system protection mechanism (such as degraded operation).

[0154] By continuously monitoring the change in electromagnetic force and calculating the compensation ratio, the system can perceive the dynamic change of electromagnetic force demand in real time, quickly adjust the compensation amount, and avoid lag or overcompensation.

[0155] The compensation gradient mechanism realizes the hierarchical adjustment of the compensation amount. For example:

[0156] Under "slow gradient", a conservative adjustment strategy is adopted (no increase in compensation amount);

[0157] Under "fast gradient", an aggressive adjustment strategy is adopted (such as significantly increasing the compensation amount and starting dynamic term compensation).

[0158] The compensation gradient indirectly reflects the influence category and strength of dynamic terms (such as inertial force and damping force) and constraint conditions (such as current upper limit and air gap constraint). For example:

[0159] A fast gradient may be caused by a sudden change in inertial force (such as load acceleration);

[0160] An excessive gradient may be triggered by a constraint condition violation (such as current overlimit).

[0161] Through gradient determination, the dominant influencing factor can be located and the coordinated control strategy can be triggered. For example:

[0162] If the gradient is dominated by inertial force, the dynamic term compensation is adjusted first;

[0163] If the gradient is dominated by the constraint condition, the constraint boundary is adjusted or the control mode is switched.

[0164] Through the gradient contrast mechanism, the system can distinguish between normal fluctuations and abnormal disturbances (such as sensor noise vs. load mutation), avoiding false triggering of compensation adjustment.

[0165] When the compensation gradient reaches "over-limit", the system can automatically start protection measures (such as limiting compensation, switching to backup control algorithm) to prevent system out-of-control.

[0166] Through gradient adjustment, the system only increases compensation when necessary, avoiding energy waste caused by invalid compensation. For example:

[0167] Under "slow gradient", a low-power compensation strategy is adopted;

[0168] Under "fast gradient", only increase compensation in critical stages.

[0169] In one embodiment of the present application, the S3 includes:

[0170] The dynamic item is continuously monitored to obtain dynamic item change data; the dynamic item includes inertial force and damping force, etc.

[0171] The dynamic item change data is subjected to change state determination to obtain dynamic item state determination information;

[0172] The dynamic item gradient corresponding instruction is triggered according to the dynamic item state determination information;

[0173] The dynamic item data when the dynamic item gradient corresponding instruction is triggered is obtained to obtain dynamic item influence data;

[0174] The dynamic item influence ratio is calculated through the dynamic item influence data, etc.; the dynamic item influence ratio is the dynamic item corresponding compensation gradient;

[0175] The calculation formula of the dynamic item influence ratio is:

[0176]

[0177] Wherein, D is the dynamic item influence ratio, ΔGZ is the final change value of the inertial force in the dynamic item change data, ΔGS is the initial change value of the inertial force in the dynamic item change data, ΔNZ is the final change value of the damping force in the dynamic item change data, and ΔNS is the initial change value of the damping force in the dynamic item change data. Wherein, the dynamic item calculation type is not limited to inertial force and damping force; when the dynamic item is n, 1 / 2=1 / n;

[0178] The constraint condition data is continuously monitored to obtain constraint condition change data. The constraint condition change data reflects dynamic adjustment of the system operation boundary. The dynamic forces such as inertial force and damping force indirectly cause the electromagnetic force compensation to break through the original calculation boundary to meet the constraint condition again by affecting the system response characteristics. The constraint condition is a condition that is usually set in advance according to historical experience in the field.

[0179] The constraint condition change data is subjected to change state determination to obtain constraint condition state determination information.

[0180] The constraint gradient corresponding instruction is triggered according to the constraint condition state determination information.

[0181] The constraint condition data when the constraint gradient corresponding instruction is triggered is obtained to obtain constraint condition influence data.

[0182] The constraint condition influence ratio is calculated through the constraint condition influence data. The constraint condition influence ratio is the constraint condition corresponding compensation gradient.

[0183] The calculation formula of the constraint condition influence ratio is:

[0184]

[0185] Wherein, B is the constraint influence ratio, ΔAmax is the actual data maximum value of the change data of the safety condition in the constraint condition, ΔAy is the safety preset threshold value of the safety condition in the constraint condition, ΔLmax is the actual data maximum value of the change data of the current condition in the constraint condition, and ΔLy is the current preset threshold value of the current condition in the constraint condition. The constraint condition calculation types are not limited to safety condition and current condition. When the constraint condition is n, 1 / 2 = 1 / n.

[0186] The dynamic item and the constraint condition have different influence modes on the electromagnetic force compensation, so the calculation modes are also different. The dynamic item is directly affected by the data variable, and the constraint condition is indirectly affected by judging whether the actual data breaks through the threshold value.

[0187] The working principle and technical effect of the above technical solution are as follows: the dynamic item includes inertial force, damping force and the like. The dynamic item is monitored in real time by a sensor (such as an accelerometer, a speed sensor and a force sensor) in the system to obtain dynamic item change data.

[0188] The dynamic item change data is subjected to feature analysis to determine the state of the dynamic item. For example:

[0189] If the inertial force change rate exceeds the threshold value, it is determined to be in a "rapid change" state.

[0190] If the damping force appears high-frequency oscillation, it is determined to be in an "oscillation" state.

[0191] Output dynamic item state determination information (e.g. "inertial force rapidly rising", "damping force high-frequency oscillation").

[0192] According to the dynamic item state determination information, trigger the corresponding dynamic item gradient instruction. For example:

[0193] If the inertial force "rapidly rises", trigger the "increase dynamic compensation" instruction;

[0194] If the damping force "oscillates", trigger the "damping suppression" instruction.

[0195] At least one trigger is a trigger dynamic item condition instruction.

[0196] When triggering the dynamic item gradient instruction, record the dynamic item data at this time (such as inertial force peak value, damping force oscillation frequency) as dynamic item influence data.

[0197] The constraint condition is the system operation boundary. Real-time monitoring of the constraint condition is carried out through sensors (such as current sensors, displacement sensors), and constraint condition change data is obtained.

[0198] Output constraint condition state determination information (whether to need to adjust the constraint condition).

[0199] According to the constraint condition state determination information, trigger the corresponding constraint gradient instruction.

[0200] At least one trigger is a trigger constraint condition instruction.

[0201] When triggering the constraint gradient instruction, record the constraint condition data at this time (such as safety threshold, current threshold) as constraint condition influence data.

[0202] By real-time monitoring of the changes of dynamic items and constraint conditions, the system can dynamically adjust the control strategy (such as dynamic compensation amount, constraint boundary) to realize the collaborative optimization of dynamic items and constraint conditions.

[0203] When the dynamic item influence is significantly enhanced (such as inertial force rapidly rising), through constraint condition influence ratio analysis, avoid compensation amount breaking through constraint boundary (such as current over-limit), ensure system safety.

[0204] Through the dynamic item influence ratio, the influence of dynamic items on the system is accurately quantified, so as to optimize the compensation amount.

[0205] Through the constraint condition influence ratio, the boundary of the compensation amount is dynamically adjusted (such as reducing the upper limit of the compensation amount to adapt to the tightening of the safety threshold), to ensure that the compensation amount is always within the constraint range.

[0206] Through real-time monitoring of dynamic items and constraint conditions and gradient instruction triggering, the system can quickly respond to external interference (such as load mutation and constraint condition change) and maintain stable operation.

[0207] When the constraint condition is triggered (such as current overrun), the system can automatically switch to a degraded operation mode (such as reducing the compensation amount) to avoid system out-of-control.

[0208] In one embodiment of the present application, the S4 comprises:

[0209] When the dynamic item gradient corresponding instruction and the constraint gradient corresponding instruction are obtained, the compensation amount influence factor is determined through the compensation amount gradient data, the dynamic item influence ratio and / or the constraint condition influence ratio; which trigger which data.

[0210]

[0211] Wherein, YS is the compensation amount influence factor coefficient, T is the corresponding compensation amount gradient range, D is the dynamic item influence ratio, and B is the constraint condition influence ratio.

[0212] When D and B do not belong to T, neither is the influence factor, when YS = 1, the influence factor is the dynamic item, when YS = 0, the influence factor is the constraint condition, and when D and B belong to T, both are influence factors.

[0213] When the compensation amount influence factor is the dynamic item, the electromagnetic force compensation data is recalculated and adjusted to obtain electromagnetic force compensation amount adjustment data.

[0214] When the compensation amount influence factor is the constraint condition, the constraint condition is adjusted to obtain constraint condition adjustment data.

[0215] When the single adjustment does not improve the effect, two influence factors can be comprehensively adjusted.

[0216] The working principle and technical effects of the above technical solution are as follows: when the compensation amount influence factor is the dynamic item, the system recalculates the electromagnetic force compensation data according to the dynamic item influence ratio. For example:

[0217] If the inertia force influence ratio increases, the electromagnetic force compensation amount is increased to offset the influence of the inertia force;

[0218] If the damping force influence ratio decreases, the electromagnetic force compensation amount is reduced to avoid overcompensation.

[0219] Output the electromagnetic force compensation amount adjustment data as the new compensation amount reference.

[0220] When the compensation amount influence factor is the constraint condition, the system adjusts the constraint condition according to the constraint condition influence ratio. For example:

[0221] If the safety threshold influence ratio decreases (constraint tightening), the upper limit of the compensation amount is reduced;

[0222] If the current threshold influence ratio increases (constraint relaxation), a higher compensation amount is allowed.

[0223] Output the constraint condition adjustment data as the new constraint boundary.

[0224] After single adjustment of the dynamic term or constraint condition, the system assesses whether the compensation amount requirement is met (e.g., whether the electromagnetic force is stable, whether the constraint condition is violated).

[0225] If the impact does not improve after single adjustment (e.g., the dynamic term compensation amount increases but still violates the constraint condition), trigger comprehensive adjustment:

[0226] Simultaneously adjust the dynamic term compensation amount and the constraint condition (e.g., appropriately relax the constraint condition to allow a higher compensation amount, while optimizing the dynamic term compensation strategy).

[0227] Coordinated optimization of dynamic term compensation amount and constraint condition (e.g., achieved through model predictive control (MPC));

[0228] Hierarchical adjustment (e.g., preferentially adjusting the dynamic term compensation amount, and if still not satisfied, adjusting the constraint condition).

[0229] Through the correlation analysis of the dynamic term influence ratio and the compensation amount gradient data, the system can accurately locate the impact of the dynamic term on the compensation amount, thereby recalculating and adjusting the electromagnetic force compensation data to ensure that the compensation amount fully matches the dynamic term requirement.

[0230] Through the correlation analysis of the constraint condition influence ratio and the compensation amount gradient data, the system can dynamically adjust the constraint condition boundary to ensure that the compensation amount is always within the safe range.

[0231] Through the coordinated adjustment of the dynamic term and the constraint condition, the system can quickly respond to external disturbances (e.g., load mutations, constraint condition changes), avoiding compensation amount breakthroughs or deficiencies.

[0232] When single adjustment is ineffective, the comprehensive adjustment mechanism ensures that the system always operates within the safe range, avoiding loss of control or failure.

[0233] One embodiment of the present application, the system comprises:

[0234] A first compensation calculation module for constructing an electromagnetic regulation system, obtaining an initial electromagnetic force, and calculating first electromagnetic force compensation data;

[0235] A comparative compensation analysis module for monitoring the change data of the initial electromagnetic force, calculating second electromagnetic force compensation data based on the change data, and obtaining the compensation amount ratio and its corresponding compensation amount gradient based on the second electromagnetic force compensation data combined with the first electromagnetic force compensation data.

[0236] An influencing factor analysis module is configured to analyze the dynamic term and the constraint condition respectively, trigger the dynamic term gradient corresponding instruction and / or the constraint gradient corresponding instruction according to the analysis information, and further obtain the dynamic term influencing ratio and / or the constraint condition influencing ratio.

[0237] A factor determination adjustment module is configured to determine the compensation influencing factor by the compensation gradient data, the dynamic term influencing ratio and / or the constraint condition influencing ratio, and further adjust the influencing data.

[0238] The working principle and technical effects of the above technical solution are as follows: an electromagnetic regulation system is constructed, an initial electromagnetic force is generated by the interaction between the electromagnetic field and the target object (such as a suspended body or a driving platform), the first electromagnetic force compensation data is calculated according to the initial state electromagnetic data of the target object, and the initial lacking electromagnetic force is offset.

[0239] The change data of the initial electromagnetic force is continuously monitored by a force sensor, the second electromagnetic force compensation data is calculated according to the monitored electromagnetic force change data, and the second compensation data reflects the dynamic demand (such as load change and external disturbance) of the electromagnetic force in the system operation process.

[0240] The ratio of the second compensation data to the first compensation data is calculated to obtain the compensation gradient.

[0241] The dynamic term (such as the inertia force and the damping force) affecting the electromagnetic force is analyzed, and the dynamic term influencing ratio is calculated.

[0242] The system operation boundary is analyzed, the constraint condition change data is obtained, and the constraint condition influencing ratio is calculated.

[0243] The dynamic term gradient corresponding instruction is triggered according to the dynamic term analysis result.

[0244] The constraint gradient corresponding instruction is triggered according to the constraint condition analysis result.

[0245] The compensation gradient data, the dynamic term influencing ratio and the constraint condition influencing ratio are analyzed and fused to determine the main factor of the current electromagnetic force compensation.

[0246] If the dynamic term influence is dominant, the dynamic term compensation strategy is preferentially adjusted.

[0247] If the constraint condition influence is significant, the compensation strategy corresponding to the constraint condition (such as reducing the upper limit of the compensation amount) is preferentially adjusted.

[0248] The electromagnetic force compensation amount is adjusted according to the analysis result to ensure that the system always meets the dynamic demand and the constraint condition.

[0249] By continuously monitoring electromagnetic force change data and calculating the compensation gradient, the compensation amount can be adjusted in real time to effectively counteract dynamic disturbances (such as sudden load changes and external vibrations) and improve the dynamic response speed of the system.

[0250] The compensation gradient mechanism avoids abrupt changes in the compensation amount, ensuring stable system operation.

[0251] By monitoring constraint change data and triggering constraint gradient commands, it can be ensured that the system always operates within the safety boundaries.

[0252] When dynamic terms conflict with constraints (such as the inertial force compensation requirement exceeding the constraint limit), the key constraints are prioritized to be satisfied through influence ratio analysis.

[0253] The influence of dynamic terms and constraints is considered at the same time, avoiding system instability caused by compensation of a single factor (such as overcompensation may occur if only inertial forces are compensated while constraints are ignored).

[0254] By using the principle of virtual displacement to predict compensation needs in advance, the system's adaptability to complex operating conditions (such as nonlinear loads and time-varying disturbances) can be enhanced.

[0255] Adjust the compensation amount according to actual needs to avoid energy waste caused by over-compensation.

[0256] Under the premise of meeting the constraints, the compensation strategy is dynamically adjusted to reduce energy consumption.

[0257] In one embodiment of the present invention, the first compensation calculation module includes:

[0258] The system construction module is used to construct an electromagnetic control system through an electromagnetic output system and an electromagnetic receiving system;

[0259] The preliminary determination module is used to obtain the initial electromagnetic force of the electromagnetic control system, calculate the initial virtual work based on the initial electromagnetic force, and determine the system equilibrium state of the electromagnetic control system based on the initial virtual work to obtain system equilibrium state determination information.

[0260] The depth determination module is used to obtain the electromagnetic compensation amount based on the system balance state determination information, and to obtain the target virtual work based on the electromagnetic compensation amount.

[0261] Based on the target virtual work, the electromagnetic control system is re-evaluated to determine the system balance state until the system balance determination information indicates a balanced state.

[0262] The initial acquisition module is used to calculate the current compensation amount based on the electromagnetic compensation amount and the Jacobian matrix when the system balance state determination information is in a balanced state. The current is then adjusted through the current compensation amount, and electromagnetic force compensation is performed to obtain the first electromagnetic force compensation data.

[0263] The working principle and technical effect of the above technical solution are as follows: an electromagnetic control system is constructed through an electromagnetic output system and an electromagnetic receiving system; the electromagnetic output system is a device that outputs current to achieve the purpose of electromagnetic control, and the electromagnetic receiving system is a device that passively performs electromagnetic force compensation.

[0264] The initial electromagnetic force of the system is obtained through sensors (such as force sensors and Hall effect sensors) in the electromagnetic control system. The initial electromagnetic force reflects the intensity of the electromagnetic interaction of the system in the initial state. Based on the principle of virtual displacement, the initial virtual work is calculated by multiplying the initial electromagnetic force by the virtual displacement. Virtual displacement is the small displacement allowed by the system under constraints, and virtual work reflects the energy change trend of the system under that displacement. Information on the system's equilibrium state (such as "unbalanced" or "balanced") is then generated.

[0265] Based on the system equilibrium determination information, the electromagnetic compensation amount is calculated. The electromagnetic compensation amount is used to counteract unbalanced forces in the system (such as increasing or decreasing electromagnetic forces).

[0266] The target virtual work is calculated based on the product of the electromagnetic compensation and the virtual displacement. The target virtual work reflects the energy change trend of the system after compensation and must satisfy the equilibrium condition.

[0267] When the system reaches equilibrium, the current compensation is calculated based on the electromagnetic compensation amount combined with the Jacobian matrix (a linearized model describing the relationship between electromagnetic force and current). The Jacobian matrix reflects the sensitivity of the electromagnetic force to current.

[0268] By adjusting the current in the electromagnetic control system (such as increasing or decreasing the driving current of the electromagnet) through current compensation, precise compensation of electromagnetic force can be achieved, thereby obtaining the first electromagnetic force compensation data.

[0269] By calculating virtual work and determining equilibrium, the system's equilibrium state can be accurately determined. Zero virtual work is a necessary and sufficient condition for system equilibrium, ensuring the accuracy of the determination result.

[0270] By iteratively calculating the target virtual work and adjusting the electromagnetic compensation, the true equilibrium state of the system is gradually approximated, thus avoiding the local optima problem that may exist in traditional methods.

[0271] By converting electromagnetic compensation quantities into current compensation quantities using the Jacobian matrix, precise control of electromagnetic force compensation is achieved. The linearization of the Jacobian matrix simplifies the control of complex nonlinear systems.

[0272] During system operation, changes in electromagnetic force can be monitored in real time and the current compensation amount can be dynamically adjusted to ensure that the electromagnetic force always meets the balance requirements.

[0273] Through closed-loop control involving virtual work balance determination and electromagnetic force compensation, the system can automatically adjust to a balanced state, effectively suppressing the impact of external disturbances on the system.

[0274] Under dynamic operating conditions, the system can quickly respond and adjust the electromagnetic force compensation amount to maintain stable operation.

[0275] In one embodiment of the present invention, the comparison compensation analysis module includes:

[0276] The second acquisition module is used to continuously monitor the initial electromagnetic force and obtain electromagnetic force change data;

[0277] The electromagnetic force change data is analyzed to determine the change state and obtain electromagnetic force state determination information.

[0278] The second electromagnetic force compensation data is obtained based on the electromagnetic force state determination information;

[0279] The gradient correspondence module is used to calculate the ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data to obtain the compensation ratio.

[0280] Obtain the gradient of the preset compensation ratio, and compare the compensation ratio with the gradient of the preset compensation difference to obtain the corresponding compensation gradient of the compensation ratio. The compensation gradient reflects the coefficients of influencing factors (influencing factors include dynamic terms and / or constraints, etc.).

[0281] The working principle and technical effect of the above technical solution are as follows: real-time monitoring of the initial electromagnetic force in the electromagnetic control system to obtain a continuous data stream of electromagnetic force changing over time.

[0282] The monitoring data is filtered (e.g., Kalman filtering, moving average filtering) and noise is reduced to eliminate noise interference and preserve the true trend of electromagnetic force changes.

[0283] State determination is made based on the characteristics of electromagnetic force change data.

[0284] The second electromagnetic force compensation data is calculated based on the above electromagnetic force compensation data calculation steps. The compensation data reflects the deviation between the current electromagnetic force demand and the initial state.

[0285] Calculate the ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data (i.e., the compensation ratio).

[0286] Preset compensation ratio gradients (such as "slow gradient", "fast gradient", "over-limit gradient"), with each gradient corresponding to a different ratio range.

[0287] The compensation ratio is compared with the preset gradient to determine the compensation gradient corresponding to the current compensation ratio. For example:

[0288] If the ratio is 30% / s, it is determined to be a "fast gradient".

[0289] The compensation gradient reflects the rate of change in electromagnetic force demand, and indirectly reflects the strength of influencing factors (such as dynamic terms and constraints).

[0290] By continuously monitoring changes in electromagnetic force and calculating the compensation ratio, the system can sense the dynamic changes in electromagnetic force demand in real time, quickly adjust the compensation amount, and avoid lag or overcompensation.

[0291] The compensation gradient mechanism enables hierarchical adjustment of the compensation amount.

[0292] The compensation gradient indirectly reflects the influence category and intensity of dynamic terms (such as inertial force and damping force) and constraints (such as current upper limit and air gap constraint).

[0293] Gradient determination can pinpoint dominant influencing factors and trigger collaborative control strategies. For example:

[0294] If the gradient is dominated by inertial forces, then the dynamic term compensation should be adjusted first.

[0295] If the gradient is dominated by constraints, then the constraint boundaries should be adjusted or the control mode should be switched first.

[0296] Through the gradient comparison mechanism, the system can distinguish between normal fluctuations and abnormal interference (such as sensor noise vs. load mutations), thus avoiding false triggering of compensation adjustments.

[0297] When the compensation gradient reaches the "exceeding limit", the system can automatically activate protection measures (such as limiting the compensation amount or switching to the backup control algorithm) to prevent the system from going out of control.

[0298] By adjusting the gradient, the system only increases the compensation amount when necessary, avoiding energy waste caused by ineffective compensation.

[0299] In one embodiment of the present invention, the influencing factor analysis module includes:

[0300] The dynamic term analysis module is used to continuously monitor dynamic terms and obtain dynamic term change data; the dynamic terms include inertial forces and damping forces, etc.

[0301] Perform change status determination on dynamic item change data to obtain dynamic item status determination information;

[0302] Trigger the corresponding instruction for the gradient of the dynamic item based on the dynamic item state determination information;

[0303] Obtain dynamic item data when the instruction corresponding to the dynamic item gradient is triggered, and obtain dynamic item impact data;

[0304] The dynamic item impact ratio is calculated using dynamic item impact data, etc.

[0305] The formula for calculating the dynamic term influence ratio is:

[0306]

[0307] Where D is the influence ratio of the dynamic term, ΔGZ is the final change value of the inertial force in the dynamic term change data, ΔGS is the initial change value of the inertial force in the dynamic term change data, ΔNZ is the final change value of the damping force in the dynamic term change data, and ΔNS is the initial change value of the damping force in the dynamic term change data. The types of dynamic terms calculated are not limited to inertial force and damping force; when there are n dynamic terms, 1 / 2 = 1 / n.

[0308] The constraint analysis module is used to continuously monitor constraint data and obtain constraint change data. The constraint change data reflects the dynamic adjustment of the system's operating boundary. Dynamic forces such as inertial force and damping force indirectly cause the electromagnetic force compensation to exceed the original calculation boundary in order to satisfy the constraint conditions again by affecting the system's response characteristics. The constraint conditions are conditions that are usually preset in the field based on historical experience.

[0309] Perform a change state determination on the constraint condition change data to obtain constraint condition state determination information;

[0310] Trigger the corresponding instruction for the constraint gradient based on the constraint condition state determination information;

[0311] Obtain constraint data when the instruction corresponding to the constraint gradient is triggered, and obtain constraint influence data.

[0312] The ratio of the influence of constraints on data is calculated by examining how constraints affect the data.

[0313] The formula for calculating the influence ratio of the constraint condition is as follows:

[0314]

[0315] Where B is the constraint influence ratio, ΔAmax is the actual maximum value of the change data of the safety condition in the constraint, ΔAy is the safety preset threshold of the safety condition in the constraint, ΔLmax is the actual maximum value of the change data of the current condition in the constraint, and ΔLy is the current preset threshold of the current condition in the constraint. The types of constraints are not limited to safety conditions and current conditions. When there are n constraints, 1 / 2 = 1 / n.

[0316] The working principle and technical effect of the above technical solution are as follows: dynamic items include inertial force, damping force, etc. The dynamic items in the system are monitored in real time by sensors (such as accelerometers, velocity sensors, force sensors) to obtain dynamic item change data.

[0317] Perform feature analysis on the dynamic changes to determine the state of the dynamic items.

[0318] Output dynamic state determination information (such as "rapid increase of inertial force" and "high-frequency oscillation of damping force").

[0319] Based on the dynamic item state determination information, the corresponding dynamic item gradient instruction is triggered.

[0320] At least one trigger is a dynamic item instruction.

[0321] When the dynamic term gradient command is triggered, the dynamic term data at this time (such as peak inertial force and damping force oscillation frequency) is recorded as dynamic term influence data.

[0322] The dynamic term influence ratio can be obtained using the formula above.

[0323] The constraints are the system operating boundaries. The constraints are monitored in real time by sensors (such as current sensors and displacement sensors) to obtain data on changes in the constraints.

[0324] Output constraint status determination information (whether constraint adjustment is required).

[0325] Based on the constraint condition status determination information, the corresponding constraint gradient command is triggered.

[0326] At least one trigger is a constraint instruction.

[0327] When the constraint gradient command is triggered, the constraint data at this time (such as safety threshold and current threshold) is recorded as constraint influence data.

[0328] The influence ratio of the constraints can be obtained using the formula above.

[0329] The constraint influence ratio reflects the degree of influence of the constraint on the system.

[0330] By monitoring changes in dynamic terms and constraints in real time, the system can dynamically adjust control strategies (such as dynamic compensation quantities and constraint boundaries) to achieve coordinated optimization of dynamic terms and constraints.

[0331] When the influence of dynamic terms increases significantly (e.g., inertial force rises rapidly), the influence ratio analysis of constraint conditions is used to prevent the compensation amount from exceeding the constraint boundary (e.g., current exceeds the limit), thus ensuring system safety.

[0332] By using the ratio of the influence of dynamic terms, the impact of dynamic terms on the system can be accurately quantified, thereby optimizing the compensation amount.

[0333] By influencing the ratio through constraints, the boundary of the compensation amount is dynamically adjusted (e.g., lowering the upper limit of the compensation amount to adapt to the tightening of the safety threshold), ensuring that the compensation amount is always within the constraint range.

[0334] Through real-time monitoring of dynamic terms and constraints and gradient command triggering, the system can quickly respond to external disturbances (such as sudden load changes and changes in constraints) and maintain stable operation.

[0335] When a constraint condition is triggered (such as current exceeding the limit), the system can automatically switch to a degraded operating mode (such as reducing the compensation amount) to avoid system loss of control.

[0336] In one embodiment of the present invention, the factor determination and adjustment module includes:

[0337] The influencing factor determination module is used to determine the influencing factors of the compensation amount by means of the compensation amount gradient data, the influence ratio of the dynamic term and / or the influence ratio of the constraint condition when the dynamic term gradient corresponding instruction and the constraint gradient corresponding instruction are obtained; whichever triggers which data is obtained.

[0338]

[0339] Where YS is the coefficient of the influencing factor of the compensation amount, T is the gradient range of the corresponding compensation amount, D is the influence ratio of the dynamic term, and B is the influence ratio of the constraint condition.

[0340] When neither D nor B belongs to T, neither is an influencing factor. When YS = 1, the influencing factor is a dynamic term. When YS = 0, the influencing factor is a constraint condition. When both D and B belong to T, both are influencing factors.

[0341] The factor adjustment module is used to recalculate and adjust the electromagnetic force compensation data when the influencing factor of the compensation amount is a dynamic item, so as to obtain the electromagnetic force compensation amount adjustment data.

[0342] When the factors affecting the compensation amount are constraints, the constraints are adjusted to obtain constraint adjustment data.

[0343] If a single adjustment fails to improve the situation, a combined adjustment of two effects can be performed.

[0344] The working principle and technical effect of the above technical solution are as follows: when the influencing factor of the compensation amount is a dynamic item, the system recalculates the electromagnetic force compensation data based on the influence ratio of the dynamic item.

[0345] Output electromagnetic force compensation adjustment data as a new compensation benchmark.

[0346] When the factors affecting the compensation amount are constraints, the system adjusts the constraints according to the ratio of their influence.

[0347] Output constraint adjustment data as the new constraint boundary.

[0348] After adjusting a single dynamic term or constraint, the system evaluates whether the compensation requirement is met (e.g., whether the electromagnetic force is stable or whether the constraint is violated).

[0349] If the impact of a single adjustment is not improved (e.g., the constraint is still violated after the dynamic term compensation is increased), then a comprehensive adjustment is triggered:

[0350] At the same time, adjust the compensation amount and constraints of the dynamic terms (such as appropriately relaxing the constraints to allow for higher compensation amounts, and optimizing the compensation strategy of the dynamic terms).

[0351] Co-optimization of dynamic term compensation and constraints (e.g., through model predictive control, MPC);

[0352] Tiered adjustment (e.g., prioritizing the adjustment of dynamic term compensation; if the conditions are still not met, then adjusting the constraints).

[0353] By analyzing the correlation between the dynamic factor influence ratio and the compensation gradient data, the system can accurately locate the impact of the dynamic factor on the compensation amount, thereby recalculating and adjusting the electromagnetic force compensation data to ensure that the compensation amount is fully matched with the dynamic factor requirements.

[0354] By analyzing the correlation between the influence ratio of constraints and the gradient data of compensation, the system can dynamically adjust the boundary of constraints to ensure that the compensation amount is always within a safe range.

[0355] Through the coordinated adjustment of dynamic terms and constraints, the system can quickly respond to external disturbances (such as sudden load changes or changes in constraints) and avoid the compensation amount from exceeding the boundary or being insufficient.

[0356] When a single adjustment is ineffective, a comprehensive adjustment mechanism is used to ensure that the system always operates within a safe range, avoiding loss of control or failure.

[0357] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An electromagnetic force compensation method based on virtual displacement, characterized in that, The method includes: S1. Construct an electromagnetic control system, obtain the initial electromagnetic force, and calculate the first electromagnetic force compensation data; S2. Monitor the change data of the initial electromagnetic force, calculate the second electromagnetic force compensation data based on the change data, and obtain the compensation ratio and its corresponding compensation gradient data based on the second electromagnetic force compensation data and the first electromagnetic force compensation data. S3. Analyze the dynamic terms and constraints respectively, and trigger the dynamic term gradient corresponding instruction and / or constraint gradient corresponding instruction according to the analysis information, thereby obtaining the dynamic term influence ratio and / or constraint influence ratio. S4. Determine the influencing factors of the compensation amount through the compensation amount gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio, and then adjust the influence data. S1 includes: The current compensation amount is calculated based on the electromagnetic compensation amount and the Jacobian matrix. The current is adjusted by the current compensation amount, and then electromagnetic force compensation is performed to obtain the first electromagnetic force compensation data. S2 includes: After calculating the initial virtual work based on the principle of virtual displacement, the system equilibrium state determination information is generated and the electromagnetic compensation is calculated. S3 includes: Continuously monitor dynamic items to obtain data on changes in dynamic items; Perform change status determination on dynamic item change data to obtain dynamic item status determination information; Trigger the corresponding instruction for the gradient of the dynamic item based on the dynamic item state determination information; Obtain dynamic item data when the instruction corresponding to the dynamic item gradient is triggered, and obtain dynamic item impact data; The dynamic item impact ratio is calculated using dynamic item impact data, etc. Continuously monitor constraint data to obtain data on changes in constraints; Perform a change state determination on the constraint condition change data to obtain constraint condition state determination information; Trigger the corresponding instruction for the constraint gradient based on the constraint condition state determination information; Obtain constraint data when the instruction corresponding to the constraint gradient is triggered, and obtain constraint influence data. Calculate the ratio of the influence of constraints on data, etc. The compensation ratio is compared with the preset gradient to determine the compensation gradient data corresponding to the current compensation ratio. The formula for calculating the dynamic term influence ratio is: Where D is the dynamic term influence ratio, ∆GZ is the final change value of inertial force in the dynamic term change data, ∆GS is the initial change value of inertial force in the dynamic term change data, ∆NZ is the final change value of damping force in the dynamic term change data, and ∆NS is the initial change value of damping force in the dynamic term change data. The formula for calculating the influence ratio of the constraint condition is as follows: Where B is the influence ratio of the constraint, ∆Amax is the actual maximum value of the change data of the safety condition in the constraint, ∆Ay is the safety preset threshold of the safety condition in the constraint, ∆Lmax is the actual maximum value of the change data of the current condition in the constraint, and ∆Ly is the current preset threshold of the current condition in the constraint. The types of constraint calculations are not limited to safety conditions and current conditions. S4 includes: The factors influencing the compensation amount are determined by the compensation amount gradient data, the influence ratio of dynamic terms, and / or the influence ratio of constraint conditions. Where YS is the coefficient of the influencing factor of the compensation amount, and T is the corresponding gradient range of the compensation amount; When neither D nor B belongs to T, neither is an influencing factor. When YS=1, the influencing factor is a dynamic term. When YS=0, the influencing factor is a constraint condition. When both D and B belong to T, both are influencing factors. When the factors affecting the compensation amount are dynamic, the electromagnetic force compensation data is recalculated and adjusted to obtain the electromagnetic force compensation amount adjustment data. When the factors affecting the compensation amount are constraints, the constraints are adjusted to obtain constraint adjustment data.

2. The electromagnetic force compensation method based on virtual displacement according to claim 1, characterized in that, S1 includes: An electromagnetic control system is constructed by using an electromagnetic output system and an electromagnetic receiving system; The initial electromagnetic force of the electromagnetic control system is obtained, the initial virtual work is calculated based on the initial electromagnetic force, and the system equilibrium state of the electromagnetic control system is determined based on the initial virtual work to obtain the system equilibrium state determination information. The electromagnetic compensation amount is obtained based on the system balance state determination information, and the target virtual work is obtained based on the electromagnetic compensation amount. Based on the target virtual work, the electromagnetic control system is re-evaluated to determine the system balance state until the system balance determination information indicates a balanced state. When the system balance state determination information indicates a balance state, the current compensation amount is calculated based on the electromagnetic compensation amount and the Jacobian matrix. The current is then adjusted using the current compensation amount, thereby performing electromagnetic force compensation and obtaining the first electromagnetic force compensation data. Among them, the electromagnetic output system is a device that outputs current to achieve electromagnetic control, and the electromagnetic receiving system is a device that passively performs electromagnetic force compensation.

3. The electromagnetic force compensation method based on virtual displacement according to claim 2, characterized in that, S2 includes: The initial electromagnetic force is continuously monitored to obtain data on changes in the electromagnetic force. The electromagnetic force change data is analyzed to determine the change state and obtain electromagnetic force state determination information. The second electromagnetic force compensation data is obtained based on the electromagnetic force state determination information; Calculate the ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data to obtain the compensation ratio. Obtain the gradient of the preset compensation ratio, compare the compensation ratio with the gradient of the preset compensation difference, and obtain the corresponding compensation gradient data of the compensation ratio.

4. The electromagnetic force compensation method based on virtual displacement according to claim 1, characterized in that, S4 includes: When the dynamic term gradient corresponding instruction and the constraint gradient corresponding instruction are obtained, the influencing factors of the compensation amount are determined by the compensation amount gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio. When the factors affecting the compensation amount are dynamic, the electromagnetic force compensation data is recalculated and adjusted to obtain the electromagnetic force compensation amount adjustment data. When the factors affecting the compensation amount are constraints, the constraints are adjusted to obtain constraint adjustment data.

5. An electromagnetic force compensation system based on virtual displacement, characterized in that, The system includes: The first compensation calculation module is used to construct the electromagnetic control system, obtain the initial electromagnetic force, and calculate the first electromagnetic force compensation data. The comparison and compensation analysis module is used to monitor the change data of the initial electromagnetic force, calculate the second electromagnetic force compensation data based on the change data, and obtain the compensation ratio and its corresponding compensation gradient data by combining the second electromagnetic force compensation data with the first electromagnetic force compensation data. The influencing factor analysis module is used to analyze dynamic terms and constraints respectively. Based on the analysis information, it triggers dynamic term gradient corresponding instructions and / or constraint gradient corresponding instructions to obtain the influence ratio of dynamic terms and / or the influence ratio of constraints. The factor determination and adjustment module is used to determine the influencing factors of the compensation amount through the compensation amount gradient data, the dynamic term influence ratio and / or the constraint condition influence ratio, and then adjust the influence data. The first compensation calculation module includes: The current compensation amount is calculated based on the electromagnetic compensation amount and the Jacobian matrix. The current is adjusted by the current compensation amount, and then electromagnetic force compensation is performed to obtain the first electromagnetic force compensation data. The comparative compensation analysis module includes: After calculating the initial virtual work based on the principle of virtual displacement, the system equilibrium state determination information is generated and the electromagnetic compensation is calculated. The influencing factor analysis module includes: The dynamic item analysis module is used to continuously monitor dynamic items and obtain data on changes in dynamic items. Perform change status determination on dynamic item change data to obtain dynamic item status determination information; Trigger the corresponding instruction for the gradient of the dynamic item based on the dynamic item state determination information; Obtain dynamic item data when the instruction corresponding to the dynamic item gradient is triggered, and obtain dynamic item impact data; The dynamic item impact ratio is calculated using dynamic item impact data, etc. The constraint analysis module is used to continuously monitor constraint data and obtain data on changes in constraint conditions. Perform a change state determination on the constraint condition change data to obtain constraint condition state determination information; Trigger the corresponding instruction for the constraint gradient based on the constraint condition state determination information; Obtain constraint data when the instruction corresponding to the constraint gradient is triggered, and obtain constraint influence data. Calculate the ratio of the influence of constraints on data, etc. The compensation ratio is compared with the preset gradient to determine the compensation gradient data corresponding to the current compensation ratio. The formula for calculating the dynamic term influence ratio is: Where D is the dynamic term influence ratio, ∆GZ is the final change value of inertial force in the dynamic term change data, ∆GS is the initial change value of inertial force in the dynamic term change data, ∆NZ is the final change value of damping force in the dynamic term change data, and ∆NS is the initial change value of damping force in the dynamic term change data. The formula for calculating the influence ratio of the constraint condition is as follows: Where B is the influence ratio of the constraint, ∆Amax is the actual maximum value of the change data of the safety condition in the constraint, ∆Ay is the safety preset threshold of the safety condition in the constraint, ∆Lmax is the actual maximum value of the change data of the current condition in the constraint, and ∆Ly is the current preset threshold of the current condition in the constraint. The types of constraint calculations are not limited to safety conditions and current conditions. The factor determination and adjustment module includes: The factors influencing the compensation amount are determined by the compensation amount gradient data, the influence ratio of dynamic terms, and / or the influence ratio of constraint conditions. Where YS is the coefficient of the influencing factor of the compensation amount, and T is the corresponding gradient range of the compensation amount; When neither D nor B belongs to T, neither is an influencing factor. When YS=1, the influencing factor is a dynamic term. When YS=0, the influencing factor is a constraint condition. When both D and B belong to T, both are influencing factors. When the factors affecting the compensation amount are dynamic, the electromagnetic force compensation data is recalculated and adjusted to obtain the electromagnetic force compensation amount adjustment data. When the factors affecting the compensation amount are constraints, the constraints are adjusted to obtain constraint adjustment data.

6. The electromagnetic force compensation system based on virtual displacement according to claim 5, characterized in that, The first compensation calculation module includes: The system construction module is used to construct an electromagnetic control system through an electromagnetic output system and an electromagnetic receiving system; The preliminary determination module is used to obtain the initial electromagnetic force of the electromagnetic control system, calculate the initial virtual work based on the initial electromagnetic force, and determine the system equilibrium state of the electromagnetic control system based on the initial virtual work to obtain system equilibrium state determination information. The depth determination module is used to obtain the electromagnetic compensation amount based on the system balance state determination information, and to obtain the target virtual work based on the electromagnetic compensation amount. Based on the target virtual work, the electromagnetic control system is re-evaluated to determine the system balance state until the system balance determination information indicates a balanced state. The initial acquisition module is used to calculate the current compensation amount based on the electromagnetic compensation amount and the Jacobian matrix when the system balance state determination information is in balance state. The current is adjusted through the current compensation amount, and then electromagnetic force compensation is performed to obtain the first electromagnetic force compensation data. Among them, the electromagnetic output system is a device that outputs current to achieve electromagnetic control, and the electromagnetic receiving system is a device that passively performs electromagnetic force compensation.

7. The electromagnetic force compensation system based on virtual displacement according to claim 5, characterized in that, The comparison compensation analysis module includes: The second acquisition module is used to continuously monitor the initial electromagnetic force and obtain electromagnetic force change data; The electromagnetic force change data is analyzed to determine the change state and obtain electromagnetic force state determination information. The second electromagnetic force compensation data is obtained based on the electromagnetic force state determination information; The gradient correspondence module is used to calculate the ratio of the second electromagnetic force compensation data to the first electromagnetic force compensation data to obtain the compensation ratio. Obtain the gradient of the preset compensation ratio, compare the compensation ratio with the gradient of the preset compensation difference, and obtain the corresponding compensation gradient data of the compensation ratio.

8. The electromagnetic force compensation system based on virtual displacement according to claim 5, characterized in that, The factor determination and adjustment module includes: The influencing factor determination module is used to determine the influencing factors of the compensation amount by means of the compensation amount gradient data, the influence ratio of the dynamic term and / or the influence ratio of the constraint condition when the dynamic term gradient corresponding instruction and the constraint gradient corresponding instruction are obtained. The factor adjustment module is used to recalculate and adjust the electromagnetic force compensation data when the influencing factor of the compensation amount is a dynamic item, so as to obtain the electromagnetic force compensation amount adjustment data. When the factors affecting the compensation amount are constraints, the constraints are adjusted to obtain constraint adjustment data.

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