Servo hydraulic multi-working condition parameter adaptive switching and correction method

Abstract

The application relates to a servo hydraulic multi-working-condition parameter adaptive switching and correction method, which comprises the following steps: monitoring and collecting system real-time data streams containing real-time hydraulic pressure, actuator speed and control response deviation; identifying the current working condition and indexing the reference control parameter based on the real-time data; running a parallel response evaluation program to generate a dynamic stability index and determine an expected performance threshold; comparing the dynamic stability index with the expected performance threshold, generating a temporary compensation coefficient to real-time correct the reference control parameter when it is confirmed that parameter mismatch occurs; monitoring the correction offset, and updating the working condition-parameter mapping database when the aging judgment condition is met. The application has the advantages of replacing manual parameter adjustment and realizing millisecond-level automatic switching of working conditions, effectively solves the parameter mismatch problem caused by equipment aging through a model self-evolution mechanism, and ensures the control precision and stability of the servo hydraulic system in the whole life cycle.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of hydraulic control, and in particular to a servo hydraulic multi-working condition parameter adaptive switching and correction method. BACKGROUND

[0002] In the field of modern industrial automation, servo hydraulic systems are widely used in injection molding machines, presses and various engineering machinery due to their high power density and precise control capabilities. Such equipment often needs to operate in complex working conditions, such as frequent switching between low-speed heavy load, high-speed light load and other modes. In order to ensure the control performance of the system under different working conditions, the control system usually needs to preset specific control parameters for each working condition, such as proportional-integral-derivative gain, pressure limit or flow limit, etc.

[0003] However, the existing parameter presetting and switching technology faces the challenge of insufficient adaptability in actual application. Traditional control strategies mostly rely on static parameter sets calibrated at the factory. Although this static mapping mechanism can provide acceptable control effect at the initial stage of the device, it fails to fully consider the time-varying nature of the physical characteristics of the hydraulic system. As the device runs for a long time, the viscosity of the hydraulic oil will change with temperature and oil aging, the hydraulic pump and valve will experience mechanical wear, and the leakage and friction characteristics of the system will also drift. These slow changes in the physical layer will cause the originally well-matched preset parameters to gradually fail.

[0004] When the static control parameters no longer match the aging physical system, the system is prone to unstable phenomena such as response lag, excessive overshoot or continuous oscillation during working condition switching. Although operators can temporarily alleviate this problem by manually adjusting control parameters, this method is low in efficiency and highly dependent on personnel experience, making it difficult to ensure consistency for different batches of equipment. In addition, for production lines with high automation requirements, frequent manual intervention will significantly reduce production efficiency. SUMMARY

[0005] In order to replace manual parameter adjustment and achieve millisecond-level automatic switching of working conditions, the present application provides a servo hydraulic multi-working condition parameter adaptive switching and correction method.

[0006] The servo hydraulic multi-working condition parameter adaptive switching and correction method provided by the present application adopts the following technical solution:

[0007] A servo hydraulic multi-working condition parameter adaptive switching and correction method, comprising the following steps:

[0008] S1. monitoring and collecting a set of system real-time data streams, wherein the system real-time data streams comprise real-time hydraulic pressure, real-time actuator velocity, and control response deviation; the control response deviation is defined as the difference between the system target pressure at the current time and the real-time hydraulic pressure, or the difference between the system target velocity at the current time and the real-time actuator velocity;

[0009] S2. accessing a preset working condition-parameter mapping database, identifying a current working condition based on the real-time hydraulic pressure and the real-time actuator velocity in the system real-time data streams, and indexing a set of reference control parameters matched with the current working condition;

[0010] S3. running a parallel response evaluation program, which calculates and generates a dynamic stability index representing the current system following performance using the control response deviation, and determines an allowable expected performance threshold based on the reference control parameters;

[0011] S4. comparing the dynamic stability index with the expected performance threshold, and confirming that parameter mismatch occurs when the dynamic stability index exceeds the expected performance threshold, and generating a temporary compensation coefficient to real-time correct the reference control parameters;

[0012] S5. monitoring the correction offset generated by the real-time correction, and updating the working condition-parameter mapping database based on the correction offset when the correction offset continuously satisfies a preset aging determination condition in multiple working cycles.

[0013] By adopting the above technical solution, by monitoring the data streams containing real-time hydraulic pressure, actuator velocity and control response deviation, and identifying the current working condition using real-time pressure and velocity to index the matched reference control parameters, automatic alignment of control configuration and actual load state is realized, and consistency deviation caused by manual parameter adjustment is avoided. The parallel response evaluation program is run to calculate the dynamic stability index representing the system following performance, and the dynamic stability index is compared with the expected performance threshold determined based on the reference parameters. When the index is detected to be out of limit, a temporary compensation coefficient is generated to real-time correct the reference control parameters. This dynamic compensation mechanism based on deviation closed loop can actively intervene in the correction of control instructions when the reference parameters cause response deterioration due to working condition mutation or model mismatch, and suppresses pressure overshoot or actuator velocity oscillation in the working condition switching process.

[0014] The correction offset generated by the real-time correction is monitored, and the working condition parameter mapping database is updated when the offset continuously meets the aging determination condition in multiple working cycles. The temporary dynamic compensation is converted into permanent reference parameter update, the originally static parameter database can evolve following the physical aging characteristics of the hydraulic system, the technical problem that the preset fixed parameters cannot adapt to long-term mechanical wear or oil characteristic drift is solved, and the control precision of the servo hydraulic system in the whole life cycle is maintained.

[0015] Optionally, the sub-step S3 comprises:

[0016] S31. In a preset transition time after the reference control parameter is loaded, the absolute value of the control response deviation is acquired in real time at a preset sampling frequency;

[0017] S32. The absolute value of the control response deviation is time-integrated or accumulated to generate the dynamic stability index;

[0018] S33. A preset parameter-tolerance correlation table is queried to acquire the maximum allowed accumulated error corresponding to the current reference control parameter, and the maximum allowed accumulated error is assigned as the expected performance threshold.

[0019] By adopting the technical scheme, the absolute value of the control response deviation is acquired in real time in a preset transition time after the reference control parameter is loaded, the time domain window of the stability evaluation is locked to the dynamic establishment process after the working condition is switched, and transient characteristics such as step response oscillation or excessively long regulation time caused by parameter mismatch are effectively captured. The absolute value of the deviation is time-integrated or accumulated to generate the dynamic stability index, the low-pass filtering characteristic of the integral algorithm is used to smooth the high-frequency noise of the sensor and the instantaneous pressure pulsation of the hydraulic pipeline, and it is ensured that the finally generated index reflects the accumulated deviation degree of the system control performance, rather than random disturbance of a single sampling point.

[0020] The parameter-tolerance correlation table is queried, and the maximum allowed accumulated error corresponding to the current reference parameter is assigned as the expected performance threshold, and a dynamic change judgment standard according to the working condition type is established. According to the physical characteristic difference under different working conditions, such as the allowed response delay under the heavy load working condition with large inertia and the strict follow-up requirement under the light load precision working condition, the corresponding stability tolerance is automatically matched. This avoids the misjudgment caused by using a single fixed threshold, prevents frequent false triggering of correction in the heavy load working condition with low precision requirement, and ensures sensitive capture of subtle instability phenomena in the high precision working condition.

[0021] Optionally, the sub-step S4 comprises:

[0022] S41. Within the preset transition time, a variable decision threshold growing with time is calculated according to the sampling time or sampling point number, and based on the expected performance threshold;

[0023] S42. The dynamic stability index is compared with the variable decision threshold in real time; when the dynamic stability index exceeds the variable decision threshold before the end of the preset transition time, it is determined that the dynamic stability index has exceeded the expected performance threshold, and it is confirmed that the parameter mismatch has occurred;

[0024] S43. When it is confirmed that the parameter mismatch has occurred, the temporary compensation coefficient capable of making the control response deviation converge is calculated, and the temporary compensation coefficient is superimposed on the reference control parameter.

[0025] By adopting the above technical solution, a time-domain tolerance envelope matched with the integral accumulation characteristics of the dynamic stability index is constructed by calculating a variable decision threshold growing with time according to the sampling progress within the preset transition time. This dynamically growing threshold setting conforms to the physical law in the response establishment process of the control system, and can effectively distinguish between the reasonable error accumulation caused by normal response delay and the abnormal divergence trend caused by parameter mismatch. Comparing the dynamic stability index with the variable decision threshold in real time enables the system to capture the instability signs in advance before the end of the transition time, without waiting for the completion of the entire sampling period. Once the index is detected to be out of limit, the temporary compensation coefficient is calculated and superimposed, realizing the in-transit intervention on the control deviation, forcing the system response to return to the convergent state before the oscillation amplitude expands, and improving the dynamic robustness in the multi-working-condition switching process.

[0026] Optionally, the sub-step of S5 comprises:

[0027] S51. After each execution of the real-time correction, the difference between the reference control parameter corrected by the temporary compensation coefficient and the original reference control parameter is calculated, and the difference is recorded as the correction offset;

[0028] S52. The correction offset is monitored in a plurality of consecutive working cycles; when the average value of the correction offset is continuously greater than a preset aging threshold, it is determined that the reference control parameter in the working condition-parameter mapping database has failed;

[0029] S53. A new reference value is calculated based on the average value of the correction offset, and the original reference control parameter in the working condition-parameter mapping database is overwritten with the new reference value.

[0030] By adopting the technical scheme, the difference between the reference control parameter modified by the temporary compensation coefficient and the original reference control parameter is calculated and recorded as a correction offset, and the dynamic intervention applied by the system in a single operation is quantified as a numerical index reflecting the gap between the physical model and the preset model. The correction offset is monitored in multiple consecutive working cycles and the average value thereof is calculated. The statistical smoothing filters incidental fluctuations caused by random load disturbance or instantaneous environmental change, and establishes a determination logic that only determines that the reference parameter is invalid when the offset exhibits persistence and the amplitude exceeds the aging threshold, thereby accurately identifying the systematic drift caused by mechanical wear, seal aging or change in hydraulic oil viscosity.

[0031] The average value of the correction offset is used to calculate a new reference value to replace the original parameter, realizing the self-adaptive iteration of the control model to the physical state of the equipment. This closed-loop updating mechanism converts the temporary compensation that only acts on the current time into permanent reference optimization for the future, enabling the working condition parameter mapping database to dynamically evolve along with the entire life cycle of the servo hydraulic system. This technical means effectively eliminates the accumulation of control errors caused by the lag of static preset parameters behind the equipment aging process, reduces the dependence of the system on real-time compensation algorithms in subsequent operation cycles, and ensures the parameter matching accuracy and control stability in long-term operation.

[0032] Optionally, the reference control parameter includes at least one of a proportional gain, an integral gain, a differential gain, and a pressure limit value.

[0033] The real-time modification in S4 refers to dynamically adjusting the proportional gain, the integral gain, the differential gain, or the pressure limit value without changing the current identified working condition.

[0034] By adopting the technical scheme, the reference control parameter is defined as the proportional gain, the integral gain, the differential gain, and the pressure limit value, which directly acts on the closed-loop transfer function of the servo hydraulic system, so that the system can directly intervene in the frequency response characteristics and steady-state accuracy of the control loop from the mathematical model level. Dynamically adjusting the above parameters without changing the current identified working condition establishes a parameter adaptive inner loop independent of the working condition switching logic. This hierarchical control architecture ensures that the parameter modification process is limited to the logical framework of the current working condition, avoiding logical shock or mode repeated jumping caused by a single parameter optimization action triggering system misjudgment of working condition change. By online fine-tuning the PID gain or pressure threshold, the damping ratio and bandwidth of the system can be changed, thereby quickly eliminating pressure overshoot and speed fluctuation caused by load mutation or parameter mismatch while maintaining the stability of the working condition logic, realizing deep self-healing and performance optimization of the control system within a single working condition.

[0035] Optionally, the sub-step of S4 further comprises:

[0036] S44. Starting a calibration cooling timer, continuously monitoring the non-zero state of the calibration cooling timer, and using the non-zero state as a shielding signal to directly lock the comparison output in S42 to maintain the inhibition state of the system parameter mismatch determination during the cooling period.

[0037] By adopting the above technical solution, a time lag protection mechanism for parameter correction action is constructed by starting a calibration cooling timer and using its non-zero state as a shielding signal to lock the comparison output. This mechanism forces the system to enter a temporary determination inhibition period after performing a correction, effectively filtering transient response oscillations or natural fluctuations in the regulation process caused by step changes in control parameters. This prevents the stability index monitoring logic from misjudging normal transient state fluctuations as new parameter mismatches, avoids control algorithm divergence or system oscillation caused by continuous and high-frequency false corrections, and ensures that each parameter adjustment has sufficient physical stabilization time.

[0038] Optionally, the sub-step of S4 further comprises:

[0039] Real-time generation of an out-of-limit comparison result between the instantaneous absolute value of the control response deviation and a preset hard safety threshold, and output of a parameter mismatch confirmation signal in response to the out-of-limit comparison result to bypass the dynamic stability index comparison logic and trigger real-time correction of the reference control parameter.

[0040] By adopting the above technical solution, an independent high-priority fast response channel is established outside the stability evaluation main channel based on the integral effect by real-time generation of an out-of-limit comparison result between the instantaneous absolute value of the control response deviation and the hard safety threshold, and direct triggering of the parameter mismatch confirmation signal using the result. This technical means bypasses the accumulation time required for dynamic stability index calculation, and can intervene immediately when the system is subjected to sudden large load shocks or severe control abnormalities causing the deviation to deviate significantly. This overcomes the inherent lag characteristic of the integral accumulation algorithm in dealing with sudden severe faults, significantly improving the emergency response speed of the servo hydraulic system under abnormal working conditions.

[0041] Optionally, after S1, there is also an effective filtering step for the real-time data stream of the system:

[0042] Real-time acquisition of an abnormal comparison result between the real-time hydraulic pressure and the change rate of the real-time actuator speed and a preset physical limit threshold, and direct execution of an interception operation on the current data frame based on the abnormal comparison result to allow only verified data streams to enter the parallel response evaluation program in S3.

[0043] By adopting the technical scheme, the abnormal data frame exceeding the physical response possibility is identified and intercepted by comparing the change rates of the hydraulic pressure and the actuator speed with the preset physical limit threshold in real time, a pre-digital cleaning mechanism for the input signal source is constructed. The step effectively eliminates the non-physical high-frequency sharp pulse generated by the industrial field electromagnetic interference or sensor instantaneous failure before the data enters the parallel response evaluation program, and cuts off the path of high-amplitude noise propagation to the downstream algorithm. Since the parallel response evaluation program involves integral or accumulation operation on the absolute value of the deviation, the filtering operation prevents the single large amplitude signal mutation from being amplified by the integral effect to cause the dynamic stability index to be high, and ensures that the subsequent parameter mismatch judgment only responds to the real hydraulic system mechanical behavior, thereby improving the signal-to-noise ratio of the adaptive control algorithm in the complex electromagnetic environment.

[0044] In summary, the present application includes at least one of the following beneficial technical effects:

[0045] 1. By running the parallel response evaluation program, the real-time closed-loop monitoring of the servo hydraulic system following performance is realized by using the comparison mechanism of the dynamic stability index and the expected performance threshold. When the parameter mismatch is detected, the temporary compensation coefficient is automatically generated to modify the reference parameter, effectively suppressing the pressure overshoot and speed oscillation in the working condition switching process, solving the technical problems of low efficiency of traditional manual parameter adjustment and difficulty of static preset parameter to adapt to load mutation;

[0046] 2. By monitoring the correction offset generated by real-time correction, and updating the working condition parameter mapping database when the aging judgment condition is met for multiple cycles, a self-evolution mechanism of the control model is constructed. This mechanism converts short-term dynamic compensation into long-term reference update, so that the control parameters can automatically follow the physical aging characteristics such as hydraulic pump wear and oil viscosity change to evolve, ensuring the control accuracy and stability of the system in the whole life cycle, overcoming the defect that the preset static model cannot cope with the long-term performance degradation of the equipment;

[0047] 3. By introducing the calibration cooling timer, the instantaneous absolute value hard safety threshold and the data stream validity filtering step, a multi-dimensional algorithm protection layer is constructed. The cooling mechanism is used to prevent repeated misjudgment caused by transient fluctuations after correction, the instantaneous hard threshold is used to compensate for the response lag of the integral algorithm under sudden failure, and the data filtering is used to eliminate electromagnetic interference noise, so as to ensure the signal-to-noise ratio and operation safety of the adaptive control strategy in complex industrial environment. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 The program block diagram of the servo hydraulic multi-working condition parameter adaptive switching and correction method in an embodiment of the present application is shown;

[0049] Figure 2A flow chart of a servo-hydraulic multi-working-condition parameter adaptive switching and correction method in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0050] The present application is further described in connection with the appended drawings. It should be understood that the specific embodiments described herein are merely illustrative of the application and should not be construed as limiting the application in any way.

[0051] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the inventive concept. As part of the description, some of the diagrams in the present disclosure are represented in block diagram form to avoid obscuring the disclosed principles. Some features of actual implementations can not be described in detail to avoid obscuring the inventive subject matter. Also, the language used in the present disclosure has been principally selected for readability and instructional purposes and can not have been selected to delineate or circumscribe the inventive subject matter, resort to the claims being necessary to determine such inventive subject matter. References in the specification to "one implementation" or "an implementation" mean that a particular feature, structure, or characteristic described is included in at least one implementation, and multiple references to "one implementation" or "an implementation" do not necessarily all refer to the same implementation.

[0052] The terms "a," "an," and "the" are not intended to refer to only a singular entity, but include the general class of which the specific example can be a part. Thus, "a" or "an" can mean any number of items, including "one," "one or more," "at least one," and "one or more than one." The term "or" means any one of the items, as well as any combination of the items, unless the context clearly indicates otherwise. The phrase "at least one of" followed by a list of two or more items means any of the items can be present, as well as any combination of the items in the list. The phrase "at least one of" does not require that all of the items in the list be present, unless specifically stated otherwise.

[0053] As a kind of power execution unit combining the precision control characteristics of servo motor with the high power density advantage of hydraulic transmission, servo hydraulic system is widely used in injection molding machine, die casting machine and various heavy engineering machinery. The system mainly controls the speed and torque of the motor through the servo driver, and then drives the hydraulic pump to output corresponding pressure oil to drive the hydraulic cylinder or hydraulic motor to execute mechanical action. However, such equipment often faces the complex challenge of multi-condition switching in actual operation. The equipment needs to frequently switch between low-speed heavy load, high-speed light load, pressure holding static and other completely different conditions, and the response characteristics of the control system required by different conditions are very different. For example, high response speed is needed to shorten the cycle in the high-speed mold closing stage, and high damping is needed to prevent pressure overshoot in the high-pressure injection stage. The existing control strategy mostly uses fixed control parameters, which cannot take into account all conditions, resulting in pressure fluctuations, action delay or oscillation when switching conditions, which seriously affects the processing accuracy and production efficiency.

[0054] Therefore, the embodiment of the present application discloses a servo hydraulic multi-condition parameter adaptive switching and correction method, referring to Figure 1 and Figure 2 , comprising the following steps S1-S5.

[0055] S1. Monitor and collect a group of system real-time data streams, wherein the system real-time data streams include: real-time hydraulic pressure, real-time actuator speed and control response deviation; the control response deviation is defined as the difference between the system target pressure at the current time and the real-time hydraulic pressure, or the difference between the system target speed at the current time and the real-time actuator speed.

[0056] The significance of collecting system real-time data streams is to provide accurate physical state basis for subsequent condition identification and closed-loop correction. Real-time hydraulic pressure directly reflects the current load condition and work object of the system, real-time actuator speed represents the motion state and flow demand of the system, and control response deviation quantifies the system following error under the current control strategy. Among them, real-time hydraulic pressure and speed are the core basis for judging the type of working condition, and control response deviation is the key index for evaluating whether the control parameters match. In order to capture the transient dynamic characteristics of the hydraulic system, the data collection frequency is usually set at a high level, for example 1kHz, that is, data is collected once every 1 millisecond. The collected various data are packaged and combined into a synchronous data frame with uniform timestamp for subsequent algorithm processing. When the sampling frequencies of various sensors are inconsistent, for example, the sampling rate of the pressure sensor is 2kHz and the sampling rate of the speed sensor is 1kHz, the system will use nearest neighbor interpolation or linear interpolation to upsample the low-frequency data, to ensure that the combined data frame is strictly aligned in time dimension.

[0057] S1. Real-time acquisition of system data stream, including real-time hydraulic pressure and real-time actuator velocity.

[0058] Real-time acquisition of abnormal comparison result between the change rate of real-time hydraulic pressure and real-time actuator velocity and preset physical limit threshold, and direct execution of interception operation on current data frame based on the abnormal comparison result, to only allow verified data stream to enter the parallel response evaluation procedure in S3.

[0059] The main purpose of validity filtering on system real-time data stream is to eliminate non-physical noise caused by industrial field electromagnetic interference or sensor failure. Hydraulic system has certain physical inertia, and the change rate of its pressure and velocity is limited by physical law, and instantaneous step mutation is impossible. If data containing high-amplitude peak noise is directly sent to subsequent integral operation link, it will cause false high stability index, and thus mis-trigger parameter correction. For example, the maximum pressure rise rate of the preset hydraulic system is 50 MPa / s. If it is monitored that the pressure data suddenly changes from 10 MPa to 30 MPa in 1 millisecond, the change rate far exceeds the physical limit threshold, the system determines that the abnormal comparison result is true, and directly intercepts the current data frame, maintains the effective value at the last moment, and thus guarantees the purity and reliability of the data stream entering the evaluation procedure.

[0060] S2. Accessing a preset working condition-parameter mapping database, identifying the current working condition based on the real-time hydraulic pressure and real-time actuator velocity in the system real-time data stream, and indexing a set of reference control parameters matched with the current working condition. The reference control parameters include at least one of proportional gain, integral gain, derivative gain, and pressure limit value.

[0061] The preset working condition-parameter mapping database refers to a structured data set stored in the internal non-volatile storage space of the controller, which establishes the logical correspondence between the physical operating state of the hydraulic system and the optimal control parameter set in the form of a multi-dimensional lookup table. The fundamental reason for constructing this database is that the servo hydraulic system has strong nonlinearity and time-varying characteristics, and a single fixed control parameter cannot meet the dynamic performance of the system under wide range of load changes. The relationship between working condition and parameter is the different demand of physical load characteristics on control stiffness and damping. For example, in the low-back-pressure fast motion stage, the hydraulic cylinder is in a low-damping state, and a small proportional gain is needed to maintain stability and prevent oscillation; while in the high-back-pressure loading stage, the equivalent stiffness of the system increases and the accuracy requirement is improved, and a large integral gain is needed to eliminate steady-state error and enhance anti-disturbance ability.

[0062] Specific working condition types are usually divided according to the threshold intervals of pressure and velocity, including but not limited to low-speed heavy-load working condition, high-speed light-load working condition, pressure-maintaining static working condition, and unloading return working condition. Taking a press as an example, the low-speed heavy-load working condition corresponds to the pressure forming process after the mold contacts the workpiece, and the high-speed light-load working condition corresponds to the empty stroke process of the slider quickly descending. A specific construction method of a working condition-parameter mapping database is usually executed in the factory calibration stage of the equipment. First, the pressure-velocity working plane of the system is divided into several discrete grid regions, and for each grid region representing a typical working condition, a set of PID gains and safety limit values that make the system performance index optimal under the working condition are obtained through step response test or relay feedback self-tuning method, and these parameters are associated and stored with the corresponding pressure and velocity intervals to form a complete mapping table.

[0063] The purpose of the S2 step is to quickly locate the current working mode of the system by using the real-time sensed physical quantities, and to load the initial reference parameters for the control loop, so as to realize automatic matching from physical state to control strategy. Its principle is based on multivariable table lookup logic, and the controller takes the real-time collected hydraulic pressure and actuator speed as index keys to perform matching retrieval in the database. The specific implementation is as follows: assuming that the real-time hydraulic pressure collected by the system is 15 MPa, and the real-time actuator speed is 2 mm / s. The controller compares these two values with the threshold conditions in the database, determines that the current state meets the set interval of pressure greater than 12 MPa and speed less than 5 mm / s, and identifies the current working condition as high-pressure slow pressing working condition. The system then indexes the reference control parameter group corresponding to this working condition, extracts the pre-stored proportional gain 1.8, integral gain 0.05, and pressure limit value 16 MPa, and immediately assigns these parameters to the control registers of the servo driver to complete the initialization and loading of the parameters.

[0064] S3. Running a parallel response evaluation program, which calculates and generates a dynamic stability index representing the current system following performance using the control response deviation, and determines an allowed expected performance threshold based on the reference control parameters.

[0065] The dynamic stability index is a cumulative quantitative value reflecting the degree of deviation of the actual output physical quantity of the servo hydraulic system from the target instruction trajectory within a specific time window, and its value directly corresponds to the degree of oscillation and the steady-state error level of the system in the dynamic response process. The expected performance threshold is the maximum deviation tolerance limit allowed by the system under a specific working condition defined according to the currently indexed reference control parameters, which establishes the quantitative boundary for determining whether the parameters are mismatched.

[0066] The step aims to build a bypass monitoring channel independent of the servo drive main control loop to evaluate the matching degree of the current loaded reference control parameters and the actual physical system in real time. Its working principle is to use the control response deviation data collected in the previous step to convert the instantaneous discrete deviation into an evaluation index reflecting the trend through mathematical operation, and dynamically match the judgment standard combined with the process requirements of the current working condition, so as to provide objective trigger basis for subsequent parameter correction.

[0067] Specifically, taking the high-pressure injection working condition of the injection molding machine as an example, this working condition requires that the hydraulic pressure strictly follow the set curve to ensure the product density. The system determines a lower expected performance threshold value from the internal database based on the reference control parameters of this working condition, for example, set the cumulative error limit value to 50 bar·ms. The parallel response evaluation program runs continuously in the background, and uses the real-time collected pressure deviation data to calculate the dynamic stability index. If the system switches to the mold opening working condition, since this stage mainly focuses on the action completion efficiency rather than the microscopic trajectory accuracy, the system will determine a higher expected performance threshold value based on the new reference parameters, for example, set to 200 bar·ms. This parameter-linked threshold setting mechanism ensures that the system maintains a sharp mismatch capture ability in high-precision working conditions, while having sufficient anti-interference margin in low-precision working conditions.

[0068] Specifically, in an embodiment, the sub-step of S3 includes S31-S33.

[0069] S31. Within a preset transition time after the reference control parameter is loaded, the absolute value of the control response deviation is obtained in real time at a preset sampling frequency.

[0070] S32. The absolute value of the control response deviation is time-integrated or accumulated to generate the dynamic stability index.

[0071] S33. Query the preset parameter-tolerance association table to obtain the maximum allowed cumulative error corresponding to the current reference control parameter, and assign it as the expected performance threshold value.

[0072] The absolute value of the control response deviation is obtained in real time at a preset sampling frequency, aiming to prevent the numerical cancellation of positive and negative deviations in the algebraic superposition process, thereby ensuring that the generated index can truly reflect the oscillation amplitude or deviation degree of the system around the target value. The control deviation of the servo hydraulic system is usually manifested as up and down fluctuations around the set value. If the algebraic sum is directly used for calculation, the positive and negative errors may add up to zero, thereby masking the actual severe oscillation. At the same time, the observation window is limited to a preset transition time after the loading of the reference control parameter, because the parameter switching moment is the most unstable stage of the system. This time window focuses on capturing the dynamic establishment process of the step response, avoiding the continuous interference of random noise during stable operation on the evaluation results.

[0073] S31 to S33 establish the conversion mechanism from instantaneous error to state evaluation. The principle is to use the integral or cumulative operation of discrete data to construct a filter with memory characteristics. By accumulating the absolute value of the deviation, the system can distinguish between transient sensor spike noise and persistent control instability. For high-frequency and zero-mean random noise, the growth rate of its cumulative value is slow; while for persistent overshoot or low-frequency large amplitude oscillation caused by parameter mismatch, the cumulative value will quickly rise. S33 matches a tailor-made qualified standard for the current control state by querying the parameter-tolerance correlation table. Since the reference parameters under different working conditions correspond to different control stiffness and physical inertia, there are natural differences in the allowed adjustment time and steady-state error, and the correlation table ensures that the threshold setting is adapted to the current physical working condition.

[0074] In specific implementation, taking the example of the aforementioned high-pressure slow pressing working condition, the system has loaded a proportional gain of 1.8 and a pressure limit value of 16 MPa. The system sets the preset transition time after parameter switching to 200 milliseconds, and the sampling frequency to 1 kHz. After the timer starts, the parallel response evaluation program collects the difference between the pressure target value and the actual value every millisecond and takes the absolute value. Assuming that the absolute value of the deviation in the first millisecond is 0.5 MPa, and in the second millisecond it is 0.4 MPa, and so on. The program continuously accumulates these values, updating the dynamic stability index in real time. At the same time, the system queries the maximum allowed cumulative error corresponding to this working condition in the parameter-tolerance correlation table according to the currently effective reference control parameter index ID, and assigns this value as the expected performance threshold, which is used as the comparison reference for subsequent judgment of whether the parameters are mismatched.

[0075] S4. Comparing the dynamic stability index with the expected performance threshold, when the dynamic stability index exceeds the expected performance threshold, confirming that parameter mismatch occurs, and generating a temporary compensation coefficient to modify the reference control parameter in real time.

[0076] The real-time correction here refers to dynamically adjusting the proportional gain, integral gain, derivative gain, or pressure limit value without changing the current identified operating condition. Due to physical phenomena such as viscosity reduction caused by hydraulic oil temperature rise, increased internal leakage caused by seal wear, etc., the actual open-loop gain of the system may drift. If the original reference parameters are maintained, the system may exhibit response delay or high-frequency oscillation. This step establishes a closed-loop feedback mechanism based on performance evaluation. When the accumulated control deviation is monitored to exceed the expected performance threshold allowed by the current operating condition, the system determines that the current physical state no longer matches the preset model. At this time, the system does not switch at the operating condition logic level, but directly introduces a correction amount at the parameter level, adjusts the transfer function gain of the controller online, forcibly pulls back the control performance, and ensures the control stability within a single operating condition.

[0077] In a specific implementation, taking the example of the high-pressure slow pressing operating condition described above, the current running reference proportional gain of the system is 1.8, and the set expected performance threshold (maximum allowed accumulated error) is 150 MPa·ms. During the transition time, the parallel response evaluation program continuously calculates the dynamic stability index. Assuming that the hydraulic pump wears out slightly, the system pressure builds up slowly, causing the absolute value of the control response deviation to increase rapidly. When the sampling reaches the 120th millisecond, the calculated dynamic stability index reaches 151 MPa·ms, exceeding the set threshold of 150 MPa·ms. At this time, the system immediately confirms that parameter mismatch has occurred. Based on the growth rate of the deviation, the compensation algorithm calculates a temporary compensation coefficient for enhancing the response, for example, a proportional gain compensation amount . The system then performs real-time correction, adjusting the currently effective proportional gain to 1.9 without interrupting or exiting the current high-pressure slow pressing operating condition, thereby compensating for the wear loss of the pump using the increased gain to make the system pressure approach the target value faster and converge the deviation.

[0078] Specifically, in an embodiment, the sub-steps of S4 include S41-S44.

[0079] S41. Within the preset transition time, a variable decision threshold that grows over time is calculated based on the sampling time or sampling point number and based on the expected performance threshold.

[0080] S42. Real-time comparison is made between the dynamic stability index and the variable decision threshold; when the dynamic stability index exceeds the variable decision threshold before the end of the preset transition time, it is determined that the dynamic stability index has exceeded the expected performance threshold, and it is confirmed that the parameter mismatch has occurred.

[0081] S43. When the parameter mismatch is confirmed, calculate the temporary compensation factor that can make the control response deviation converge, and superimpose the temporary compensation factor on the reference control parameter.

[0082] S44. Start a calibration cooling timer, continuously monitor the non-zero state of the calibration cooling timer, and directly lock the comparison output in S42 using the non-zero state as a shielding signal to maintain the inhibition state of the system parameter mismatch determination during the cooling period.

[0083] The expected performance threshold refers to the maximum cumulative absolute value of the control response deviation allowed by the system based on the process accuracy requirements of the current working condition within the full preset transition time window, which represents the total tolerance budget of the system during the entire dynamic establishment process. The variable decision threshold that increases over time is the tolerance limit allocated according to the current time progress at each sampling moment during the transition time. The rule of increasing over time is usually set as a linear increasing function, i.e. the variable decision threshold at the current time is equal to the expected performance threshold multiplied by the ratio of the current sampling time to the total preset transition time. This design aims to build a dynamic time-domain decision envelope to ensure that the decision logic can run throughout the entire response establishment process, rather than only at the end point. The calculation of the temporary compensation factor uses a proportional mapping algorithm based on the deviation degree, i.e. according to the amplitude of the dynamic stability index exceeding the variable decision threshold, the required gain adjustment or limit adjustment is calculated according to the preset sensitivity coefficient to produce a correction effect sufficient to offset the current control error.

[0084] The purpose of steps S41 to S44 is to establish a fast correction mechanism with pre-judgment and anti-disturbance capabilities. By dividing the static total threshold into a dynamic decision line that grows over time, the system can identify the instability trend before the end of the transition time. Once the current cumulative error exceeds the tolerance quota at the current time point, the system determines the parameter mismatch and intervenes in the correction, thereby significantly shortening the duration of the abnormal state and preventing the deviation from further diverging in subsequent time. At the same time, the calibration cooling timer is introduced to solve the problem of transient oscillation after parameter correction. After performing a correction, the change in the physical state of the system will cause fluctuations in the sensor data. The cooling mechanism forces the decision logic to be locked, giving the system sufficient physical stabilization time to prevent continuous and false secondary corrections caused by normal fluctuations during the adjustment process.

[0085] In the specific implementation, the scenario continues to use the high-pressure slow pressing mode described above. The total preset transition time set by the system is 200 ms, and the expected performance threshold is 150 MPa·ms. When the sampling reaches the 100th millisecond, the system calculates the variable judgment threshold at the current time according to the linear growth rule as 75 MPa·ms. At this time, the dynamic stability index calculated by the parallel response evaluation program is 80 MPa·ms. Although the end of 200 ms has not been reached, and 80 MPa·ms has not exceeded the total threshold of 150 MPa·ms, since it has exceeded the dynamic quota of 75 MPa·ms at the current time, the system determines that a parameter mismatch has occurred. Based on the excess of 5 MPa·ms, the system calculates a temporary compensation coefficient of 0.1 increase in the proportional gain, and immediately superimposes it on the reference parameter, so that the proportional gain changes from 1.8 to 1.9. At the same time of executing the correction action, the system starts a calibration cooling timer with a duration of 500 ms. Within the 500 ms, even if the subsequent pressure data fluctuates temporarily due to the change in gain, the comparison output of S42 will be shielded until the cooling timer is zero, and the system resumes the monitoring function of the parameter mismatch.

[0086] Optionally, in some embodiments, the sub-step of S4 further includes:

[0087] generating an out-of-limit comparison result between the instantaneous absolute value of the control response deviation and a preset hard safety threshold in real time, and outputting a confirmation signal of the parameter mismatch in response to the out-of-limit comparison result, to bypass the comparison logic of the dynamic stability index and preferentially trigger real-time correction of the reference control parameter.

[0088] The out-of-limit comparison result is a logical decision state indicating whether the instantaneous value of the control response deviation at the current time has broken through the physical limit boundary allowed by the safe operation of the system. Its physical meaning is to characterize whether the servo hydraulic system has encountered a sudden load shock, an abnormal sensor signal, or a serious actuator stuck fault, and this result directly reflects whether the system currently has a transient severe instability that may cause equipment damage or product scrap. Bypassing means establishing a fast execution channel in the control logic independent of the calculation process of the dynamic stability index, that is, without waiting for the integral or cumulative process of the absolute value of the deviation to be completed, and without relying on the variable judgment threshold that increases over time, but directly making decisions based on the out-of-limit state of the instantaneous value. Real-time correction of the reference control parameter refers to the emergency parameter adjustment action performed to cope with sudden abnormalities, which is usually manifested as a significant reduction in the proportional gain to suppress oscillation, or a direct forced reduction of the pressure limit value to the safety interval to prevent the fault from expanding.

[0089] The purpose of this step is to make up for the response lag defect of the dynamic stability index based on integral effect when dealing with sudden and large faults. Although the integral-based evaluation method has good smoothing effect on noise, it needs a certain time window to accumulate errors, which may cause the protection action to be too slow when facing millisecond-level sudden faults. By introducing an out-of-limit comparison mechanism based on instantaneous absolute value, the system builds a dual monitoring architecture of trend evaluation and instantaneous protection in parallel. Once the instantaneous deviation breaks through the hard safety threshold, the system immediately determines that the parameter is seriously mismatched and triggers the correction, thereby ensuring the dynamic safety of the system under extreme abnormal working conditions.

[0090] In specific implementation, continue to use the scenario of the aforementioned high-pressure slow pressing working condition, the system sets the expected performance threshold (integral accumulation limit) to 150 MPa·ms, and sets a preset hard safety threshold to 20 MPa. This means that although the system allows to accumulate larger errors within a time period, it does not allow any single moment of pressure deviation to exceed 20 MPa. During operation, it is assumed that the hydraulic pipeline is blocked due to foreign matter, causing the system pressure to suddenly rise within 1 millisecond, so that the instantaneous absolute value of the control response deviation reaches 25 MPa. Although the cumulative value of the dynamic stability index at this time may not have reached the threshold of 150 MPa·ms, or even not reached the variable judgment threshold at the current moment, since the instantaneous value 25 MPa has exceeded the hard safety threshold 20 MPa, the system generates a true out-of-limit comparison result in real time. In response to this result, the system immediately outputs a confirmation signal of parameter mismatch, bypasses the subsequent integral calculation logic, and preferentially triggers emergency correction, for example, forcibly reduces the pressure limit value from the current 16 MPa to 5 MPa, and at the same time resets the proportional gain to 0, to immediately unload and protect the hydraulic element.

[0091] S5. Monitor the correction offset generated by the real-time correction, and when the correction offset continuously meets the preset aging judgment condition in multiple working cycles, update the working condition-parameter mapping database based on the correction offset.

[0092] This step aims to build a long-period parameter self-evolution mechanism for the servo hydraulic system, to solve the technical problem that the preset static reference parameters cannot follow the slow drift of the physical characteristics of the equipment. The mechanical wear of the hydraulic pump, the increase of the matching gap of the valve core, and the long-term attenuation of the viscosity of the hydraulic oil, will cause permanent changes in the open-loop gain and response characteristics of the system. Although the previous real-time correction step can compensate for the control deviation in a single run, if the reference model is not updated, the system must repeatedly go through the process of mismatch-correction every time it starts the working condition, which reduces the control efficiency. The working principle of this step is based on the time domain statistical analysis of the correction offset. By monitoring the distribution characteristics of the correction amount in multiple working cycles, the random deviation caused by load fluctuation is distinguished from the systematic deviation caused by equipment aging. Only when the correction offset shows the characteristics of persistent existence and stable amplitude, the system determines that the physical model has undergone irreversible changes, and the temporary compensation amount is solidified into the database, thereby realizing the self-iteration of the control strategy.

[0093] In a specific implementation, taking the example of the high-pressure slow pressing working condition mentioned above, it is assumed that in the S4 step, in order to compensate for the pressure response delay caused by the wear of the hydraulic pump, the system real-time corrects the proportional gain from the reference value 1.8 to 1.9. At this time, the system records the correction offset generated by this correction as +0.1. The S5 step continuously monitors the next several working cycles in the background, for example, the monitoring window is set to 50 molding cycles. If in the subsequent 50 cycles, the S4 step triggers similar correction actions every time the system enters the high-pressure slow pressing working condition, and the correction offset generated is always maintained within the interval of +0.08 to +0.12, it indicates that the gain compensation of about +0.1 is not to cope with occasional disturbances, but is necessary to maintain the new normal of the system's normal performance. At this time, the system determines that the offset meets the preset aging determination condition, and immediately performs the database update operation, permanently modifying the reference proportional gain corresponding to this working condition in the working condition-parameter mapping database from 1.8 to 1.9. In the 51st cycle and subsequent runs, the system will directly load the new reference value 1.9, thereby eliminating the initial parameter mismatch, and no longer triggering the real-time correction logic of S4.

[0094] Specifically, in an embodiment, the S5 sub-step includes S51-S53.

[0095] S51. After each execution of the real-time correction, calculate the difference between the reference control parameter corrected by the temporary compensation coefficient and the original reference control parameter, and record the difference as the correction offset.

[0096] S52. Monitor the correction offset in multiple consecutive working cycles, and determine that the reference control parameter in the working condition-parameter mapping database has been invalidated when the average value of the correction offset continuously exceeds a preset aging threshold.

[0097] S53. Calculate a new reference value based on the average value of the correction offset, and overwrite the original reference control parameter in the working condition-parameter mapping database with the new reference value.

[0098] S51-S53 constitute the specific execution logic of model self-correction, which aims to provide a quantitative, statistical and updated closed-loop path to eliminate the permanent parameter deviation caused by physical aging of the system. The working principle is first to convert the fuzzy control intervention into an accurate numerical indicator, i.e. the correction offset, through difference calculation. Then, the offset is filtered using a multi-cycle statistical averaging algorithm. Since the hydraulic system is often affected by random factors such as oil temperature fluctuations or power grid voltage fluctuations, a single or small number of corrections is not enough to prove that the system characteristics have fundamentally changed. Therefore, S52 sets an aging threshold and a continuous monitoring mechanism to ensure that only when the offset shows statistical significance and persistence, the database is updated. Finally, S53 performs a substantive write operation to solidify the verified experience value as a new reference value, thereby completing the adaptive fitting of the control model to the physical system.

[0099] In a specific implementation, continue to use the scenario of the aforementioned high-pressure slow pressing working condition, and the original reference proportional gain is 1.8. In the first working cycle, due to the detection of pressure response delay, the S4 step corrects the proportional gain in real time to 1.92, at which time S51 calculates the correction offset of this time as +0.12. In the next monitoring window, for example, in the next 50 working cycles, the system continuously monitors the correction offset each time. Assuming that in these 50 cycles, due to the influence of hydraulic pump wear, the system needs to increase the gain to about 1.9 each time to meet the expected performance threshold, and the arithmetic mean of the 50 correction offsets calculated is +0.11. The system presets an aging threshold of 0.05 for the proportional gain. At this time, since the average offset +0.11 continuously exceeds the aging threshold 0.05, the system executes the S52 determination logic, and determines that the original reference value 1.8 in the database has been invalidated. Then in the S53 step, the system calculates a new reference value of 1.8 plus the average offset +0.11, i.e. 1.91, and uses the new value 1.91 to overwrite the original 1.8 in the database. Since the 51st cycle, the system will directly use 1.91 as the initial gain, thereby meeting the control requirements without the need for real-time correction.

[0100] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0101] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit it; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A servo-hydraulic multi-working-condition parameter adaptive switching and correction method, characterized in that, The method comprises the following steps: S1. monitoring and collecting a set of system real-time data streams, wherein the system real-time data streams comprise real-time hydraulic pressure, real-time actuator speed, and control response deviation; the control response deviation is defined as the difference between the system target pressure at the current time and the real-time hydraulic pressure, or the difference between the system target speed at the current time and the real-time actuator speed; S2. accessing a preset working condition-parameter mapping database, identifying the current working condition based on the real-time hydraulic pressure and the real-time actuator speed in the system real-time data streams, and indexing a set of reference control parameters matched with the current working condition; S3. running a parallel response evaluation program, which calculates and generates a dynamic stability index representing the current system following performance using the control response deviation, and determines an allowable expected performance threshold based on the reference control parameters; S4. comparing the dynamic stability index with the expected performance threshold, and confirming that parameter mismatch occurs and generating a temporary compensation coefficient to real-time correct the reference control parameters when the dynamic stability index exceeds the expected performance threshold; S5. monitoring the correction offset generated by the real-time correction, and updating the working condition-parameter mapping database based on the correction offset when the correction offset continuously satisfies a preset aging determination condition in multiple working cycles.

2. The servo-hydraulic multi-working-condition parameter adaptive switching and correction method according to claim 1, characterized in that, The sub-step of S3 comprises: S31. real-time obtaining the absolute value of the control response deviation at a preset sampling frequency within a preset transition time after the reference control parameters are loaded; S32. performing time integration or accumulation operation on the absolute value of the control response deviation to generate the dynamic stability index; S33. querying a preset parameter-tolerance correlation table to obtain the maximum allowable cumulative error corresponding to the current reference control parameters, and assigning it as the expected performance threshold.

3. The servo-hydraulic multi-condition parameter adaptive switching and correction method according to claim 2, characterized in that, The sub-step of S4 comprises: S41. calculating a variable determination threshold that increases with time according to the sampling time or the number of sampling points and based on the expected performance threshold within the preset transition time; S42. real-time comparing the dynamic stability index with the variable determination threshold; when the dynamic stability index exceeds the variable determination threshold before the end of the preset transition time, it is determined that the dynamic stability index has exceeded the expected performance threshold, and it is confirmed that the parameter mismatch occurs; S43. when it is confirmed that the parameter mismatch occurs, calculating the temporary compensation coefficient that can make the control response deviation converge, and superimposing the temporary compensation coefficient on the reference control parameters.

4. The servo-hydraulic multi-condition parameter adaptive switching and correction method according to claim 1, characterized in that, The sub-step of S5 comprises: S51. calculating the difference between the reference control parameters corrected by the temporary compensation coefficient and the original reference control parameters after each execution of the real-time correction, and recording the difference as the correction offset; S52. Monitor the correction offset over a plurality of consecutive working cycles, and determine that the reference control parameter in the working condition-parameter mapping database has been invalidated when the average value of the correction offset continuously exceeds a preset aging threshold; S53. Calculate a new reference value based on the average value of the correction offset, and use the new reference value to replace the original reference control parameter in the working condition-parameter mapping database.

5. The servo-hydraulic multi-condition parameter adaptive switching and correction method according to claim 1, characterized in that, The reference control parameter includes at least one of proportional gain, integral gain, derivative gain, and pressure limit value; The real-time correction in S4 refers to dynamic adjustment of the proportional gain, integral gain, derivative gain, or pressure limit value without changing the currently identified working condition.

6. The servo-hydraulic multi-condition parameter adaptive switching and correction method according to claim 3, characterized in that, The sub-step of S4 further includes: S44. Start a calibration cooling timer, continuously monitor the non-zero state of the calibration cooling timer, and use the non-zero state as a shielding signal to directly lock the comparison output in S42, so as to maintain the inhibition state of the system parameter mismatch determination during the cooling period.

7. The servo-hydraulic multi-condition parameter adaptive switching and correction method according to claim 3, characterized in that, The sub-step of S4 further includes: Real-time generate an out-of-limit comparison result between the instantaneous absolute value of the control response deviation and a preset hard safety threshold, and output a confirmation signal of the parameter mismatch in response to the out-of-limit comparison result, so as to bypass the comparison logic of the dynamic stability indicator and preferentially trigger the real-time correction of the reference control parameter.

8. The servo-hydraulic multi-condition parameter adaptive switching and correction method according to claim 1, characterized in that, After S1, there is further included a validity filtering step for the real-time data stream of the system: Real-time obtain an abnormal comparison result between the change rate of the real-time hydraulic pressure and the real-time actuator speed and a preset physical limit threshold, and directly perform an interception operation on the current data frame based on the abnormal comparison result, so as to only allow verified data stream to enter the parallel response evaluation procedure in S3.

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