A manipulation load friction force simulation method, system, device and medium based on rate of change feedback adjustment

Abstract

The present application relates to a kind of based on rate of change feedback regulation's steering load friction simulation method, system, equipment and medium, method includes: the speed generated by motor of flight simulator is obtained and is normalized;After the speed after normalization is optimized and error and error differential processing;PID control output calculation is then carried out, and proportion term and differential term are obtained;Using slip rate limiter to calculate correction factor and for adjusting proportion term and differential term;Using the proportion term and differential term after adjustment to calculate normalized friction, and convert into actual friction.The method of the present application can automatically adjust friction model parameters according to actual operating state, without manual intervention, greatly reduce the debugging workload;Through dynamic parameter adjustment, more aggressive parameter setting is used when stable, realize faster friction commutation, while automatically relaxing parameter when steering load system tends to be unstable can ensure stability.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of friction force adjustment of flight simulators, and particularly relates to a control load friction force simulation method, system, device and medium based on rate feedback adjustment. BACKGROUND

[0002] Flight simulators play an important role in pilot training, and the control load system thereof needs to truly restore the force feedback when pilots operate an aircraft. The accurate simulation of friction force directly affects the realism and effect of training. According to relevant aviation regulations, the control load system needs to accurately simulate the static and dynamic control force response characteristics that are extremely close to those of a real aircraft under different flight conditions, which puts forward higher requirements for the simulation of friction force.

[0003] Due to the difference in mechanical structure between the simulator and the real aircraft, friction force cannot be generated naturally as in the real aircraft and needs to be artificially simulated by a motor or the like. The accuracy of friction force simulation not only affects the operation experience of pilots, but also relates to the effectiveness of training and the service life of equipment. If the friction force simulation is improper, high-frequency oscillation of the control stick may occur, affecting the realism of training, and even accelerating the wear of mechanical parts.

[0004] At present, the mainstream friction force simulation methods mostly adopt the Coulomb friction model and its improved models, such as introducing a speed ramp-in area and a dead zone, to reduce the problem of high-frequency oscillation at low speed. Although these methods improve the simulation effect of friction force to some extent, they still have obvious deficiencies: first, the parameters (such as the dead zone and the ramp-in speed) are difficult to adjust, the system is sensitive to parameter changes, and phenomena such as high-frequency oscillation or unrealistic friction force reversal are likely to occur; second, the parameters are usually fixed values, lacking self-adaptive ability, and it is difficult to cope with changes in system state and external environment; third, in order to improve the simulation effect, it is often necessary to upgrade the hardware such as motors and sensors, resulting in increased cost and being unrealistic for deployed equipment.

[0005] Therefore, the main technical problem faced by the current control load system is to achieve high-precision, stable and realistic simulation of friction force without relying on hardware upgrades. This problem needs to be solved through more advanced software algorithms and self-adaptive control methods to meet the continuous improvement needs of flight simulators for the performance of control load systems. SUMMARY

[0006] In order to overcome the problems existing in the prior art, the present application provides a control load friction force simulation method, system, device and medium based on rate feedback adjustment, which is used to overcome the existing defects.

[0007] A control load friction force simulation method based on rate feedback adjustment, the method comprising the steps of:

[0008] S1. Obtain the speed generated by the motor of the flight simulator;

[0009] S2. Normalize the speed;

[0010] S3. Optimize the normalized speed and calculate the error and error differential;

[0011] S4. Perform PID control output calculation on the error and speed differential values obtained through error and error differential processing to obtain the proportional term and the differential term;

[0012] S5. Calculate the correction factor using the slip rate limiter;

[0013] S6. Adjust the proportional term and the differential term using the correction factor;

[0014] S7. Calculate the normalized friction force using the adjusted proportional term and the differential term, and convert it to the actual friction force.

[0015] According to the aspect and any possible implementation manner described above, an implementation manner is further provided, wherein the S2 comprises normalizing the speed and mapping it to the range of [-1, 1];

[0016]

[0017] wherein: is the normalized speed, and v is the original speed, is the speed threshold triggering the maximum friction.

[0018] According to the aspect and any possible implementation manner described above, an implementation manner is further provided, wherein the S3 specifically comprises:

[0019] S31. Obtain the processing value using the exponential curve mixing method ;

[0020] S32. Calculate the error and the differential value of the current period;

[0021] S33. Perform low-pass filtering on the differential value to obtain the speed differential value .

[0022] According to the aspect and any possible implementation manner described above, an implementation manner is further provided, wherein the S31 obtains the processing value using the exponential curve mixing method , and the calculation formula is: , wherein

[0023] ​, wherein, is an exponential curve function, is a parameter of the exponential curve, and is a known quantity.

[0024] Aspects and any possible implementation modes as described above further provide an implementation mode, the error and the differential value are calculated according to the following formulas, respectively:

[0025] ;

[0026] , wherein, is an error of a previous period.

[0027] Aspects and any possible implementation modes as described above further provide an implementation mode, S4 specifically comprises:

[0028] S41. According to the error and the speed differential value , a proportional term and a differential term are calculated.

[0029] S42. The proportional term and the differential term are normalized to obtain normalized and .

[0030] Aspects and any possible implementation modes as described above further provide an implementation mode, S5 specifically comprises:

[0031] S51. According to a ratio of a change amount of the signal to a time step, a slip rate is calculated by using a low-pass filter.

[0032] S52. The slip rate is compared with a preset maximum slip threshold , a slip rate greater than or equal to the maximum slip threshold is taken as a positive slip rate, a slip rate less than the maximum slip threshold is taken as a negative slip rate, and the positive slip rate and the negative slip rate are attenuated to obtain an attenuated maximum positive slip rate and a maximum negative slip rate .

[0033] S53. According to the maximum slip threshold , a correction factor variable and a correction gain constant , a correction factor is calculated.

[0034] The present invention also provides a simulation system for manipulating load friction based on rate of change feedback regulation. The system is used to implement the method and includes the following modules:

[0035] The acquisition module is used to acquire the speed generated by the motors of the flight simulator;

[0036] A normalization processing module is used to normalize the speed;

[0037] The optimization calculation module is used to optimize the normalized speed and then perform error and error differentiation processing.

[0038] The PID control output calculation module is used to calculate the PID control output based on the error and speed derivative values ​​obtained after error and error derivative processing, and to obtain the proportional term and derivative term.

[0039] The first calculation module is used to calculate the correction factor using the slip ratio limiter;

[0040] The adjustment module is used to adjust the proportional and differential terms using correction factors.

[0041] The second calculation module is used to calculate the normalized friction force using the adjusted proportional and differential terms, and then convert it into the actual friction force.

[0042] The present invention also provides an electronic device, the electronic device comprising:

[0043] Memory, which stores executable instructions;

[0044] A processor that executes the executable instructions in the memory to implement the method.

[0045] The present invention also provides a computer storage medium storing a computer program, the computer program being executed by a processor to implement the method described.

[0046] Beneficial effects of the present invention

[0047] The present invention provides a method for simulating the frictional force of control load based on rate of change feedback regulation, comprising the following steps: acquiring the speed generated by the motor of a flight simulator; normalizing the speed; optimizing the normalized speed and performing error and error derivative processing; calculating the proportional and derivative terms of the error and speed derivative values ​​obtained after error and error derivative processing using PID control output; calculating a correction factor using a slip ratio limiter; adjusting the proportional and derivative terms using the correction factor; and calculating the normalized frictional force using the adjusted proportional and derivative terms and converting it into actual frictional force. The method of the present invention has the following beneficial effects:

[0048] 1) Adaptive parameter adjustment: The load control system can automatically adjust the friction model parameters according to the actual operating conditions without manual intervention, which greatly reduces the amount of debugging work.

[0049] 2) Rapid friction reversal: Through dynamic parameter adjustment, more aggressive parameter settings can be used when the system is stable to achieve faster friction reversal. At the same time, the parameters are automatically relaxed when the load system tends to be unstable to ensure stability.

[0050] 3) Improved system robustness: It has the ability to adapt to changes in the parameters of the control load system (such as friction, clearance, etc.) and can adapt to changes in the characteristics of the control load system caused by long-term operation.

[0051] 4) Suppressing High-Frequency Oscillations: The slip ratio limiter can effectively detect and suppress high-frequency oscillations in the controlled load system, improving system stability. Specifically, when oscillations are detected, the correction factor is reduced. Reduce control gain; the slip ratio limiter uses a time window and event logging mechanism to accurately identify oscillation characteristics; the peak hold and decay mechanism ensures that the manipulated load system can gradually recover to a high-performance state.

[0052] 5) High versatility: Due to the use of normalization processing, this algorithm can be applied to different channels and different types of control load systems, and has wide adaptability.

[0053] 6) No additional hardware required: Implemented purely through software algorithms, performance improvements can be achieved without upgrading hardware, significantly reducing costs.

[0054] 7) High computational efficiency: The algorithm has a simple structure, low computational load, and is easy to implement in real-time control of the load system. Attached Figure Description

[0055] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0056] To better understand the technical solution of this invention, the content of this invention includes, but is not limited to, the specific embodiments described below. Similar technologies and methods should be considered within the scope of protection of this invention. To make the technical problems to be solved, the technical solutions, and advantages of this invention clearer, a detailed description will be provided below in conjunction with the accompanying drawings and specific embodiments.

[0057] It should be understood that the embodiments described in this invention are merely some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0058] The present invention provides a method for simulating the frictional force of a manipulating load based on rate of change feedback regulation, the method comprising the following steps:

[0059] S1. Obtain the speed generated by the motors of the flight simulator;

[0060] S2. Normalize the speed;

[0061] S3. Optimize the normalized speed and process the error and error derivative;

[0062] S4. Perform PID control output calculation on the error and speed derivative values ​​obtained after error and error derivative processing to obtain the proportional term and derivative term;

[0063] S5. Calculate the correction factor using the slip ratio limiter;

[0064] S6. Adjust the proportional and differential terms using correction factors;

[0065] S7. Calculate the normalized friction force using the adjusted proportional and differential terms, and convert it into the actual friction force.

[0066] Further, S2 includes: normalizing the velocity and mapping it to the range [-1, 1]:

[0067]

[0068] in: It is the normalized velocity, and v is the original velocity. It is the speed threshold at which the maximum friction force is triggered.

[0069] Furthermore, S3 specifically includes:

[0070] S31. The normalized velocity is processed using an exponential curve mixing method to obtain the processed value. ;

[0071] S32. Adopt Calculate the error of the current period and differential value ;

[0072] S33. On the differential value Perform low-pass filtering to obtain the velocity derivative. .

[0073] Furthermore, S31 uses an exponential curve mixing method to obtain the processed value. The calculation formula used is: ,in

[0074]

[0075] In the formula, It is an exponential curve function. The parameters of the exponential curve are known quantities.

[0076] Furthermore, error and differential value The calculation formulas are as follows:

[0077] ;

[0078] In the formula, It is the error from the previous cycle.

[0079] Furthermore, S4 specifically includes: S41. Based on the error and velocity differential value Calculate the proportional term and differential terms ;

[0080] S42. Comparative Term and differential terms Perform normalization to obtain the normalized result. and .

[0081] Furthermore, S5 specifically includes:

[0082] S51. The slip ratio is calculated based on the ratio of the signal change to the time step and using low-pass filtering. ;

[0083] S52. Slip ratio With the preset maximum slip threshold By comparing slip rates greater than or equal to the maximum slip threshold, positive slip rates are defined as slip rates; slip rates less than the maximum slip threshold are defined as negative slip rates. The positive and negative slip rates are then attenuated to obtain the attenuated maximum positive slip rate. and maximum negative slip ratio ;

[0084] S53. Based on the maximum slip threshold Correction factor variables and corrected gain constant Calculate the correction factor .

[0085] This invention provides an adaptive friction compensation method, solving the problem that traditional methods require hardware upgrades. This method dynamically adjusts the friction model parameters by real-time monitoring of system oscillation characteristics, maximizing the friction simulation effect while ensuring the stability of the controlled load system. The specific process is as follows:

[0086] Step 1. Speed ​​normalization processing

[0087] The velocity is normalized and mapped to the range [-1, 1].

[0088] (1)

[0089] in: is the normalized velocity, dimensionless; v is the original velocity, in meters per second. This is the speed threshold that triggers maximum friction (i.e., the asymptotic speed), measured in meters per second. Speed ​​v refers to the actual speed of the motor (or actuator) in the flight simulator's control load system during the current cycle. This speed is measured in real-time by existing high-precision sensors (such as encoders or speed sensors), reflecting the true motion state of the control mechanism at the current moment.

[0090] Step 2. Exponential Curve Hybrid Optimization

[0091] To simultaneously achieve the dual objectives of suppressing zero-position oscillations and rapidly reaching the amplitude limit, this invention employs an exponential curve hybrid method to process the normalized velocity, as expressed below:

[0092] (2)

[0093] in: This represents an exponential curve function, used to convert linear inputs... Convert to a non-linear output; This indicates the result after processing with an exponential curve. The parameter representing the exponential curve controls the curve shape, and in this invention, it is set to 0.

[0094] The specific definition of an exponential curve function is a weighted mixture of linear and cubic components:

[0095] (3)

[0096] when When the input is equal to the output, the curve is linear; when the output is equal to the input, the curve is linear. When the input is zero, the output is the cube of the input, changing slowly near zero and rapidly away from zero. In this invention, Setting it to 0 maintains a linear relationship; this parameter can be adjusted as needed to obtain different response characteristics.

[0097] Step 3. Error and error differential calculation

[0098] The goal of this invention is to make the processed value The value approaches 0, therefore the calculation error is:

[0099] (4)

[0100] The differential value of the error is obtained by dividing the difference between the current error and the error of the previous cycle by the time step, as shown in the following expression:

[0101] (5)

[0102] in It is the system error of the controlled load, which is dimensionless; It is the error from the previous cycle, and it is dimensionless. It is the time step, measured in seconds (s).

[0103] To reduce the impact of noise, the above differential value is processed using a low-pass filter:

[0104] (6)

[0105] in, It is the filtered velocity derivative, in Hertz (Hz). It is the difference between the current error and the error of the previous cycle divided by the time step, in Hertz (Hz). These are low-pass filter coefficients calculated based on the time step and filter frequency, and are dimensionless.

[0106] Among them, the low-pass filter coefficients The calculation formula is:

[0107] (7)

[0108] Where: dt is the time step, in seconds (s); It is the filter cutoff frequency of the low-pass filter, measured in Hertz (Hz), and is set to 20Hz in this invention.

[0109] The present invention uses the aforementioned low-pass filter to smooth the differential signal, reduce the influence of high-frequency noise, and prevent the control load system from over-responding to brief disturbances.

[0110] Step 4. PID control output calculation

[0111] Based on the error and its derivative, calculate the proportional and differential terms and output them:

[0112] (8)

[0113] (9)

[0114] in: It is a proportional output, dimensionless; It is a differential output, dimensionless.

[0115] It is the proportional gain, which is set to 1.0 in this invention; It is the differential gain, which is set to 0.0 in this invention.

[0116] To ensure that the output amplitude does not exceed 1, for and The terms are normalized to obtain the normalized result. and :

[0117] (10)

[0118] (11)

[0119] (12)

[0120] The above normalization process ensures that the sum of the proportional and differential terms is within the range of [-1, 1], thus avoiding the output exceeding the maximum value of the friction force.

[0121] 5. Slew Limiter Implementation

[0122] This invention employs a slip ratio limiter to dynamically monitor and adjust the parameters of the controlled load system. The specific steps are as follows:

[0123] 5.1. Slip Ratio Calculation

[0124] This step detects whether the system oscillates by tracking the rate of change (slip rate) of the input signal. Its recursive expression is:

[0125] (13)

[0126] For slip ratio, This is the input value from the previous cycle; the input signal for the current cycle is updated using this formula. The low-pass filter coefficient is calculated using the aforementioned formula (7).

[0127] 5.2. Oscillation Event Detection

[0128] When the slip ratio exceeds the preset maximum slip ratio threshold At any given time, a timestamp is recorded to analyze the frequency and pattern of the oscillations: if the oscillation exceeds a set threshold in the positive direction, it is recorded as a positive event; if it exceeds a threshold in the negative direction, it is recorded as a negative event. In the slip rate limiter, the core of oscillation event detection is determining whether the slip rate `filtered_slew_rate` exceeds the preset maximum slip rate threshold `slew_rate_max`. This maximum slip rate threshold includes the positive maximum slip rate threshold `max_pos_slew_rate` and the negative maximum slip rate threshold `max_neg_slew_rate`.

[0129] Positive events: When the slip rate filtered_slew_rate is greater than or equal to max_pos_slew_rate, it is recorded as a positive event, and the timestamp of the event is recorded. The essence of a positive event is that the slip rate signal exceeds the maximum positive slip rate threshold in the positive direction, indicating that the system may have experienced a rapid positive change or oscillation.

[0130] Negative events: When the slip rate filtered_slew_rate is less than or equal to -max_neg_slew_rate, it is recorded as a negative event, and the timestamp of the event is also recorded. The essence of a negative event is that the slip rate signal exceeds the maximum negative slip rate threshold in the negative direction, indicating that the system may have experienced a rapid negative change or oscillation.

[0131] The determination of positive and negative events is related to the actual value of the current slip ratio. Only when the absolute value of the slip ratio exceeds the threshold will it be recorded as an event. Each "crossing" that exceeds the threshold is considered an event.

[0132] The system has recorded the most records. A positive and One negative event, preferred This is sufficient to identify a complete oscillation cycle, meaning that the entire process records at most two positive and two negative events, thus capturing a complete oscillation cycle. Specifically, the method involves analyzing the alternation and intervals of positive and negative events using a timestamp sequence to determine if the system exhibits periodic oscillations. A complete oscillation cycle is characterized by the slip rate signal first exceeding a threshold positively (positive event), then exceeding the threshold negatively (negative event), and so on. By statistically analyzing the time intervals between positive and negative events, the frequency and pattern of the oscillations can be estimated.

[0133] 5.3. Peak Tracking and Attenuation

[0134] Record the observed maximum positive slip rate and maximum negative slip ratio The natural decay is determined based on the time constant, as expressed below:

[0135] (14)

[0136] (15)

[0137] in, The attenuation coefficient is calculated based on the time step and the slip ratio time constant, and the calculation formula is:

[0138] (16)

[0139] The set slip ratio time constant determines the decay rate of the slip ratio peak. This decay mechanism allows the load control system to "forget" past oscillation events and gradually recover to a higher performance state.

[0140] 5.4. Calculation of Correction Factor

[0141] use , The system dynamically records the maximum positive and negative slip rates over a period of time. These two values ​​reflect the system's maximum rate of change in the recent past. Their purpose is to provide a reference for calculating the correction factor in this step. The maximum positive and negative slip rates in step 5.3 are used to reflect the system's recent extreme dynamic behavior, providing basic data for the dynamic adjustment of the correction factor in this step. Without these peaks, the adaptability and robustness of the correction factor would decrease.

[0142] The peak tracking in step 5.3 provides the data basis for the dynamic adjustment of the correction factor in this step, and the two are closely related. The correction factor Dmod is directly used for the dynamic adjustment of the output gain of the PID controller for friction compensation, which is one of the core mechanisms of the adaptive vibration suppression of this invention, and the dynamic adjustment of the correction factor is only triggered when the absolute value of the slip ratio exceeds the threshold (i.e., when a positive / negative event occurs).

[0143] When a slip ratio greater than or equal to a preset maximum threshold is detected, a correction factor is calculated. This is used to reduce the output gain of the dynamic adjustment controller (in this invention, a friction-compensated PID controller) to prevent the system from becoming unstable due to high-frequency oscillations. The formula for calculating the correction factor is:

[0144] (17)

[0145] in: It is the preset maximum slip ratio threshold.

[0146] It is the corrected slip ratio; This is the correction gain constant, with a default value of 1.5.

[0147] Corrected slip ratio The calculation formula is as follows:

[0148] modifier_slew_rate=max_pos_slew_rate - max_neg_slew_rate (18)

[0149] Among them, when equal hour, At this point, the output is not modified;

[0150] when Greater than hour, At this point, reduce the output gain;

[0151] when Much larger hour, This means a significant reduction in output gain.

[0152] 5.5. Time Window Mechanism

[0153] The slip ratio limiter is set by a time window ( The frequency of oscillation is determined by a value (default is 100 milliseconds). Oscillation in the load control system is caused by excessively high control gain in the motor speed control circuit. When oscillation occurs, the control output repeatedly reverses direction, which inevitably leads to a high slip ratio.

[0154] If multiple oscillation events are detected within the window time, the load manipulation system further reduces the correction factor to more effectively suppress high-frequency oscillations.

[0155] Step 6. Adaptive parameter update

[0156] The correction factor of the slip ratio limiter is directly applied to the proportional and derivative control outputs:

[0157] (19)

[0158] (20)

[0159] in It is the correction factor calculated by the slip ratio limiter, and its range is [0,1].

[0160] When the load control system detects oscillations The value is reduced, thereby reducing the control output and making the load control system more stable. If there is oscillation, it indicates that the motor control parameters (P-term output and D-term output) of the load control system are too high and the slip ratio SlewRate exceeds the limit value. According to the formula (17) described above, this makes Dmod less than 1, thereby reducing the output of P-term and D-term.

[0161] When the load control system is running stably A value close to 1 allows for more aggressive control output to achieve better friction simulation.

[0162] Step 7. Friction Calculation and Denormalization

[0163] Finally, the normalized friction force is calculated using proportional and differential terms, and then denormalized to obtain the actual friction force output.

[0164] (twenty one)

[0165] (twenty two)

[0166] in: It is the normalized friction force obtained from the final calculated output, which is calculated based on the proportional control output and correction factor, and is dimensionless.

[0167] It is the final actual control output frictional force, measured in Newtons (N).

[0168] It is the maximum value of friction, measured in Newtons (N).

[0169] This frictional force It is directly corresponding to the current motor speed v, meaning that the friction force calculated at each moment is based on the actual speed of the current operating mechanism. This friction force normalization process can be applied to different channels and different types of operating load systems, improving versatility.

[0170] This invention normalizes the speed to a standard range, improving the method's versatility. It employs exponential curve hybrid optimization, using nonlinear curves to process the normalized speed, achieving the dual goals of smooth transition at low speeds and rapid response at high speeds. A slip ratio limiter monitors the system's oscillation state in real time, automatically and dynamically adjusting the friction response parameters. When the system tends to oscillate, the slip ratio limiter automatically increases the asymptotic parameter (by reducing the control gain) to ensure stability; when the system stabilizes, the parameter is decreased (by restoring the control gain) to obtain a more accurate friction simulation. This adaptive mechanism allows the system to always operate at the optimal balance between stability and performance.

[0171] Preferably, at the confirmation speed Furthermore, this invention can also use different asymmetric velocities and dead-zone parameters for positive and negative motions to adapt to the asymmetric characteristics of the system. The specific implementation is as follows:

[0172] (twenty three)

[0173] in, It is the positive trigger speed threshold; It is the negative trigger speed threshold.

[0174] This method can better adapt to the different frictional characteristics that the control system may have in different directions, thus improving the realism of the simulation.

[0175] Preferably, frequency domain analysis methods such as FFT (Fast Fourier Transform) or wavelet analysis can be used to replace the slip rate limiter in this invention, identifying the system's oscillation characteristics and adjusting parameters through spectral analysis. This method can identify the oscillation frequency more accurately, but the computational complexity is higher. Specifically, this can be achieved by performing real-time spectral analysis on the velocity signal to extract the main oscillation frequency components:

[0176] (twenty four)

[0177] Then, the correction factor is calculated based on the spectral characteristics:

[0178] (25)

[0179] in: It is the spectrum of the velocity signal; and These are warning and danger oscillation frequency thresholds; It is a function that calculates the correction factor based on the spectral characteristics, and it is a general function.

[0180] This method can more accurately identify the frequency characteristics of system oscillations and suppress oscillations in specific frequency bands, but it requires higher computational resources.

[0181] Preferably, the slip ratio limiter can be replaced with a fuzzy controller, which dynamically adjusts the friction model parameters according to fuzzy rules. The inputs to the fuzzy controller may include the current oscillation degree, oscillation frequency, and rate of change of velocity, and the output is the parameter adjustment amount.

[0182] The fuzzy rules are designed as follows:

[0183] - If the oscillation is low and the rate of change is small, then keep the current parameters;

[0184] - If the oscillation is moderate, slightly reduce the gain parameter;

[0185] - If the oscillation is high, significantly reduce the gain parameter;

[0186] - If there is no oscillation for a long time, gradually increase the gain parameter;

[0187] Fuzzy controllers can take into account multiple indicators to achieve more complex decision-making logic and adapt to more complex system characteristics.

[0188] As an embodiment of the present invention, the present invention also discloses a simulation system for manipulating load friction based on rate of change feedback regulation. The system is used to implement the method and includes the following modules:

[0189] The acquisition module is used to acquire the speed generated by the motors of the flight simulator;

[0190] The normalization module is used to normalize the speed.

[0191] The optimization calculation module is used to optimize the normalized speed and then perform error and error differentiation processing.

[0192] The PID control output calculation module is used to calculate the PID control output based on the error and speed derivative values ​​obtained after error and error derivative processing, and to obtain the proportional term and derivative term.

[0193] The first calculation module is used to calculate the correction factor using the slip ratio limiter;

[0194] The adjustment module is used to adjust the proportional and differential terms using correction factors.

[0195] The second calculation module is used to calculate the normalized friction force using the adjusted proportional and differential terms, and then convert it into the actual friction force.

[0196] As an embodiment of the present invention, the present invention also discloses an electronic device, the electronic device comprising: a memory storing executable instructions;

[0197] A processor that executes the executable instructions in the memory to implement the method of the present invention.

[0198] As an embodiment of the present invention, the present invention also discloses a computer storage medium storing a computer program, which is executed by a processor to implement the method described in the present invention.

[0199] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0200] The foregoing description illustrates and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for simulating the frictional force of manipulated loads based on rate of change feedback regulation, characterized in that, The method includes the following steps: S1. Obtain the speed generated by the motors of the flight simulator; S2. Normalize the speed; S3. Optimize the normalized speed and process the error and error derivative, specifically including: S31. The normalized velocity is processed using an exponential curve mixing method to obtain the processed value. The calculation formula used is: ,in In the formula, It is an exponential curve function. The parameters of the exponential curve are known quantities. S32. Adopt Calculate the error of the current period and differential value The error and differential value The calculation formulas are as follows: ； In the formula, It is the error from the previous cycle; S33. On the differential value Perform low-pass filtering to obtain the velocity derivative. ; S4. Perform PID control output calculation on the error and speed derivative values ​​obtained after error and error derivative processing to obtain the proportional term and derivative term; S5. Calculate the correction factor using the slip ratio limiter; S6. Adjust the proportional and differential terms using correction factors; S7. Calculate the normalized friction force using the adjusted proportional and differential terms, and convert it into the actual friction force.

2. The method according to claim 1, characterized in that, S2 includes: normalizing the velocity and mapping it to the range [-1, 1]. , in, It is the normalized velocity, and v is the original velocity. It is the speed threshold at which the maximum friction force is triggered.

3. The method according to claim 1, characterized in that, S4 specifically includes: S41. Based on the error and velocity differential value Calculate the proportional term and differential terms ; S42. Comparative Term and differential terms Perform normalization to obtain the normalized result. and .

4. The method according to claim 3, characterized in that, S5 specifically includes: S51. The slip ratio is calculated based on the ratio of the signal change to the time step and using low-pass filtering. ; S52. Slip ratio With the preset maximum slip threshold By comparing slip rates greater than or equal to the maximum slip threshold, positive slip rates are defined as slip rates; slip rates less than the maximum slip threshold are defined as negative slip rates. The positive and negative slip rates are then attenuated to obtain the attenuated maximum positive slip rate. and maximum negative slip ratio ; S53. Based on the maximum slip threshold Correction factor variables and corrected gain constant Calculate the correction factor .

5. A simulation system for manipulating load friction force based on rate of change feedback regulation, characterized in that, The system is used to implement the method according to any one of claims 1-4, and includes the following modules: The acquisition module is used to acquire the speed generated by the motors of the flight simulator; A normalization processing module is used to normalize the speed; The optimization calculation module is used to optimize the normalized speed and then perform error and error differentiation processing. The PID control output calculation module is used to calculate the PID control output based on the error and speed derivative values ​​obtained after error and error derivative processing, and to obtain the proportional term and derivative term. The first calculation module is used to calculate the correction factor using the slip ratio limiter; The adjustment module is used to adjust the proportional and differential terms using correction factors. The second calculation module is used to calculate the normalized friction force using the adjusted proportional and differential terms, and then convert it into the actual friction force.

6. An electronic device, characterized in that, The electronic device includes: Memory, which stores executable instructions; A processor that executes the executable instructions in the memory to implement the method of any one of claims 1-4.

7. A computer storage medium, characterized in that, The medium stores a computer program, which is executed by a processor to implement the method described in any one of claims 1-4.

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