A predictive control method, device and medium for an electro-hydraulic servo system

Abstract

This invention discloses a model predictive control method, device, and medium for an electro-hydraulic servo system, relating to the field of electro-hydraulic servo model prediction technology. The method includes: acquiring data based on the electro-hydraulic servo system; defining a state variable vector based on the resultant force formed by the equivalent chamber pressure difference; discretizing the vector using the forward Euler method; constructing a piston force balance equation; updating the state variable vector data; setting the relationship equation between the valve core opening and the control voltage in the electronic control domain; updating the flow rate of the hydraulic cylinder into the upper and lower chambers; and reconstructing and updating the state variable vector. The method of this invention, through the combined use of the force balance equation in the mechanical domain and the compensation signal in the electronic control domain, allows the voltage change issued by the controller to be equivalent to direct control of the output force. Through the integrated fusion of static mapping functions and dynamic compensation functions, the compensated voltage drive signal can maintain ideal linearity in steady state and correct hysteresis errors in real time during dynamic changes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electro-hydraulic servo model prediction, and in particular to an electro-hydraulic servo system model prediction control method, device and medium. BACKGROUND

[0002] The electro-hydraulic servo system is widely used in aerospace, engineering machinery, precision manufacturing and process control fields. The system controls hydraulic actuators through electrical signals to realize the unification of high dynamic response and large power output. Traditional electro-hydraulic servo control adopts proportional-integral-derivative (PID) control or fuzzy control to realize accurate tracking of displacement, speed or force. Due to the significant nonlinear characteristics of the electro-hydraulic servo system, such as the compressibility of hydraulic oil, the dead zone effect caused by the gap change between the valve core and the valve port, the saturation characteristics and the hysteresis effect, with the progress of sensing and computing technology, model-based predictive control (MPC) is gradually introduced into the field of electro-hydraulic servo system control because it can realize optimal control under constraints and has good feedforward compensation characteristics.

[0003] However, traditional MPC often requires a high-precision system model in the electro-hydraulic servo scene. The nonlinear valve port flow characteristics and dynamic hysteresis characteristics are often difficult to accurately describe through an analytical model, leading to prediction error accumulation and control performance degradation. The dynamic response characteristics of the valve port dead zone, saturation zone and their transition region are not fully considered, making the controller output unable to accurately reflect the real flow change of the valve port. In addition, the system state update is often based on single feedback of the hydraulic cylinder pressure or displacement, and a complete state variable vector is not constructed to reflect the coupling characteristics between the mechanical domain, hydraulic domain and electrical control domain, resulting in insufficient state prediction accuracy and affecting control stability and tracking accuracy. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides an electro-hydraulic servo system model prediction control method, device and medium to solve the problem that traditional MPC often requires a high-precision system model in the electro-hydraulic servo scene, the nonlinear valve port flow characteristics and dynamic hysteresis characteristics are often difficult to accurately describe through an analytical model, leading to prediction error accumulation and control performance degradation, the dynamic response characteristics of the valve port dead zone, saturation zone and their transition region are not fully considered, making the controller output unable to accurately reflect the real flow change of the valve port, in addition, the system state update is often based on single feedback of the hydraulic cylinder pressure or displacement, and a complete state variable vector is not constructed to reflect the coupling characteristics between the mechanical domain, hydraulic domain and electrical control domain, resulting in insufficient state prediction accuracy and affecting control stability and tracking accuracy.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present invention provides a model predictive control method for an electro-hydraulic servo system, comprising:

[0008] Data acquisition is performed based on the electro-hydraulic servo system. The state variable vector is defined according to the resultant force formed by the pressure difference in the equivalent chamber. The discretization is performed by the forward Euler method to construct the piston force balance equation, update the state variable vector data, set the relationship equation between the valve core opening and the control voltage in the electronic control domain, update the flow rate of the hydraulic cylinder into the upper and lower chambers, and reconstruct and update the state variable vector.

[0009] Extract control voltage signal sequence data and measured flow signal data at the valve port, identify dead zone and saturation zone, divide the response range of the valve port, construct a unified static mapping function, introduce valve core displacement sensor signal to establish a first-order inertial dynamic compensation model, define dynamic compensation function, and integrate the static mapping function and dynamic compensation function to form a compensated voltage drive signal.

[0010] Based on the physical limitations of the controller specifications, determine the actual voltage signal sent to the servo valve driver, update the reconstructed state variable vector, and perform state prediction.

[0011] Based on the deviation between the predicted state and the desired state, a predicted voltage signal is output.

[0012] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, the following steps are included: defining the state variable vector, discretizing it using the forward Euler method, constructing the piston force balance equation, updating the state variable vector data, setting the relationship equation between the valve core opening and the control voltage in the electronic control domain, updating the flow rate of the hydraulic cylinder into the upper and lower chambers, and reconstructing and updating the state variable vector, including...

[0013] The state variable vector is defined based on the resultant force formed by the hydraulic cylinder piston displacement data, piston speed data, and equivalent chamber pressure difference;

[0014] The pressure state values ​​of the two chambers are calculated based on the pressure data collected from the two chambers of the hydraulic cylinder and the effective area of ​​the hydraulic cylinder piston.

[0015] Discretization is performed using the forward Euler method to obtain the pressure values ​​of the upper and lower chambers, and the piston force balance equation is constructed to update the piston velocity, piston acceleration, and the resultant force formed by the pressure difference in the equivalent chamber.

[0016] Establish the relationship equation between the valve core opening degree and the control voltage in the electronically controlled domain, and update the flow rate of the hydraulic cylinder into the upper and lower chambers;

[0017] The state variable vector is reconstructed and updated based on the updated flow rate in the upper and lower chambers of the hydraulic cylinder, as well as the resultant force formed by the piston speed, piston acceleration, and equivalent chamber pressure difference.

[0018] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, the following steps are included: identifying dead zones and saturation zones, dividing the response range of the valve orifice, constructing a unified static mapping function, introducing valve core displacement sensor signals to establish a first-order inertial dynamic compensation model, defining a dynamic compensation function, and integrating the static mapping function and the dynamic compensation function to form a compensated voltage drive signal, including...

[0019] Based on the reconstruction and update of the state variable vector, the control voltage signal sequence data and the measured flow signal data of the valve port are extracted to identify the dead zone and saturation zone. The dead zone is judged according to the lower limit of the valve port flow detection resolution, and the saturation zone is judged according to the flow change rate threshold.

[0020] Based on the positive and negative boundary voltages of the dead zone and the positive and negative boundary voltages of the saturation zone, the response interval of the valve orifice is divided as linear region data, and the linear region gain is output by fitting using the least squares method.

[0021] A unified static mapping function is constructed based on the linear region gain, and the dead zone and saturation zone are linearly extended and compensated.

[0022] For the static mapping function, a first-order inertial dynamic compensation model is established by introducing the valve core displacement sensor signal, and the model is discretized using the forward Euler method to define the dynamic compensation function.

[0023] The static mapping function and the dynamic compensation function are integrated and fused to form the compensated voltage drive signal.

[0024] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, wherein: determining the actual voltage signal sent to the servo valve driver based on the physical limitations of the controller specifications includes,

[0025] Based on the voltage drive signal of the integrated compensation, physical limits are applied according to the maximum and minimum voltages specified by the controller, and the actual voltage signal sent to the servo valve driver is determined.

[0026] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, the updated and reconstructed state variable vector performs state prediction, including:

[0027] The reconstructed state variable vector is updated based on the voltage signal sent to the servo valve driver, and state prediction is performed through recursive calculation.

[0028] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, the step of outputting a predicted voltage signal based on the deviation between the predicted state and the desired state includes:

[0029] Set the desired state and define the objective function, evaluate the deviation between the predicted state and the desired state and the change of the control quantity, define the constraints to minimize the objective function, and output the predicted voltage signal.

[0030] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, the defined constraint conditions include:

[0031] The boundary values ​​of the resultant force formed by the hydraulic cylinder piston displacement data, piston speed data, and equivalent chamber pressure difference are all defined based on the safety range standards for equipment use.

[0032] As a preferred embodiment of the model predictive control method for the electro-hydraulic servo system described in this invention, the step of data acquisition based on the electro-hydraulic servo system includes:

[0033] For the hydraulic cylinder of the electro-hydraulic servo system, piston displacement and piston speed data are collected. At the same time, pressure data for the two chambers of the hydraulic cylinder are collected. For the control signal generator, the input voltage of the electro-hydraulic servo valve is collected. For the hydraulic circuit of the electro-hydraulic servo system, hydraulic pressure data is collected.

[0034] In a second aspect, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the electro-hydraulic servo system model predictive control method as described in the first aspect of the present invention.

[0035] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the electro-hydraulic servo system model predictive control method as described in the first aspect of the present invention.

[0036] The beneficial effects of this invention are as follows: By combining the force balance equation in the mechanical domain with the compensation signal in the electronic control domain, the voltage change issued by the controller can be equivalent to direct control of the output force. Through the integrated fusion of the static mapping function and the dynamic compensation function, the compensated voltage drive signal can maintain ideal linearity in steady state and correct hysteresis error in real time during dynamic changes. The fusion compensation mechanism isomorphizes the static structural parameters and dynamic response parameters, making the compensation output have time-domain continuity and amplitude consistency, thereby forming a stable voltage-flow mapping relationship throughout the entire control range. Through this combination, the system can maintain consistent valve flow control characteristics under different load and oil temperature conditions, significantly improving the linearity and dynamic predictability of the parallel valve control system. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Fig. 1 This is a flowchart illustrating the model predictive control method for the electro-hydraulic servo system in Example 1.

[0039] Fig. 2 This is a schematic diagram of the state feedback process of the model predictive control method for the electro-hydraulic servo system in Example 1. Detailed Implementation

[0040] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0041] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0042] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0043] Example 1, referring to Figs. 1-2 This is the first embodiment of the present invention, which provides a model predictive control method for an electro-hydraulic servo system, comprising the following steps:

[0044] S1. Data acquisition is performed based on the electro-hydraulic servo system. The state variable vector is defined according to the resultant force formed by the pressure difference of the equivalent chamber. The vector is discretized by the forward Euler method. The piston force balance equation is constructed, the state variable vector data is updated, the relationship equation between the valve core opening and the control voltage in the electronic control domain is set, the flow rate of the hydraulic cylinder into the upper and lower chambers is updated, and the state variable vector is reconstructed and updated.

[0045] Preferably, data acquisition is based on an electro-hydraulic servo system, including:

[0046] For the hydraulic cylinder of the electro-hydraulic servo system, piston displacement and piston speed data are collected. At the same time, pressure data for the two chambers of the hydraulic cylinder are collected. For the control signal generator, the input voltage of the electro-hydraulic servo valve is collected. For the hydraulic circuit of the electro-hydraulic servo system, hydraulic pressure data is collected.

[0047] Furthermore, a state variable vector is defined, discretized using the forward Euler method, and a piston force balance equation is constructed. The state variable vector data is updated, the relationship equation between the valve core opening and control voltage in the electronic control domain is set, the flow rates into the upper and lower chambers of the hydraulic cylinder are updated, and the state variable vector is reconstructed and updated, including…

[0048] The state variable vector, defined by the resultant force formed from the hydraulic cylinder piston displacement data, piston velocity data, and equivalent chamber pressure difference, is expressed as follows:

[0049] ;

[0050] in, Represents a vector of state variables. This indicates the piston displacement data of the hydraulic cylinder. This represents piston speed data. The resultant force formed by the pressure difference in the equivalent cavity is represented by k, which represents the discrete-time index.

[0051] The pressure state values ​​of the two chambers of the hydraulic cylinder are calculated based on the pressure data collected from both chambers and the effective area of ​​the hydraulic cylinder piston, and are expressed as follows:

[0052] ;

[0053] ;

[0054] in, This represents the rate of change of the upper chamber pressure with time t. This represents the rate of change of the lower chamber pressure with time t. This indicates the bulk modulus of elasticity of hydraulic oil. and These represent the instantaneous volumes of the upper and lower chambers of the hydraulic cylinder, respectively. and These represent the flow rates into the upper and lower cavities, respectively. Indicates the effective area of ​​the hydraulic cylinder piston;

[0055] Discretization is performed using the forward Euler method to obtain the pressure values ​​of the upper and lower chambers. The piston force balance equation is then constructed, updating the piston velocity, piston acceleration, and the resultant force formed by the equivalent chamber pressure difference, expressed as:

[0056] ;

[0057] ;

[0058] ;

[0059] ;

[0060] ;

[0061] ;

[0062] in, This represents the pressure in the upper cavity at discrete time point k. Indicates the sampling time interval. The lower chamber pressure is represented at discrete time point k, and M represents the equivalent mass of the hydraulic cylinder and load. This represents the rate of change of the piston speed over time t. Indicates the coefficient of viscous friction. Indicates external load force. This indicates the updated piston speed. This indicates the updated piston acceleration. This represents the resultant force formed by the updated equivalent cavity pressure difference;

[0063] The relationship equation between the valve core opening and the control voltage in the electronically controlled domain is established, and the flow rates into the upper and lower chambers of the hydraulic cylinder are updated, expressed as:

[0064] ;

[0065] ;

[0066] ;

[0067] in, This indicates the valve core displacement data. The voltage displacement data gain is provided by the servo valve's factory specifications. Indicates the control voltage signal. and These represent the flow of the updated hydraulic cylinder into the upper and lower chambers, respectively. The flow coefficient is determined based on historical experience. Indicates the width of the valve port. Indicates the system oil supply pressure. Indicates the return oil pressure. Indicates the density of hydraulic oil;

[0068] Based on the updated flow rates in the upper and lower chambers of the hydraulic cylinder, as well as the resultant force formed by the piston speed, piston acceleration, and equivalent chamber pressure difference, the state variable vector is reconstructed and updated, as follows:

[0069] ;

[0070] ;

[0071] ;

[0072] in, Represents the position update vector. This represents the velocity update vector. This represents the vector of state variables that are reconstructed and updated.

[0073] By synchronously integrating the discrete modeling results of the mechanical domain, hydraulic domain, and electronic control domain with the parallel valve characteristic mapping and the "dead zone-saturation" compensation mechanism, the energy transfer relationship inside the system no longer depends on single-domain approximation, but achieves the isochronous phase response consistency among the three domains of electrical signal, fluid power, and mechanical motion, thereby significantly reducing the coupling delay error between multiple domains.

[0074] By directly introducing the compensated driving voltage into the discretized equation, a linear correspondence is maintained between the pressure change rate in the hydraulic domain and the valve opening change, thereby realizing a proportional consistency mapping from the electronic control domain to the hydraulic domain, effectively eliminating the oil flow delay and system hysteresis error caused by the dead zone;

[0075] By using a static-dynamic isomorphic compensation method, static nonlinearity (such as dead zone and saturation) and dynamic nonlinearity (such as valve core inertia and fluid compression) are synchronously corrected under the same mapping framework. By combining the discrete update of the two-chamber pressure in the hydraulic domain with the compensated flow input, the pressure integral error term is self-consistently corrected in numerical iteration, realizing real-time self-compensation of nonlinear pressure accumulation error, avoiding pressure drift problem in multi-cycle operation, and improving long-term stability.

[0076] By combining the force balance equations in the mechanical domain with the compensation signals in the electronic control domain, the voltage changes issued by the controller can be equivalent to direct control of the output force. By using the flow mapping function of the parallel valve group and the discrete state prediction model in a unified manner, the nonlinear characteristics of each valve port are converted into deterministic linear gains in the overall system prediction matrix, realizing the equivalent linearization of the multi-valve parallel system. This eliminates the need for additional parameter identification between predictive control and actual execution.

[0077] Preferably, constraints are defined, including:

[0078] The boundary values ​​of the resultant force formed by the hydraulic cylinder piston displacement data, piston speed data, and equivalent chamber pressure difference are all defined based on the safety range standards for equipment use.

[0079] S2, extract the control voltage signal sequence data and the measured flow signal data of the valve port, identify the dead zone and saturation zone, divide the response range of the valve port, construct a unified static mapping function, introduce the valve core displacement sensor signal to establish a first-order inertial dynamic compensation model, define the dynamic compensation function, and integrate the static mapping function and the dynamic compensation function to form the compensated voltage drive signal.

[0080] Preferably, dead zone and saturation zone identification is performed, the response range of the valve port is divided, a unified static mapping function is constructed, a first-order inertial dynamic compensation model is established by introducing the valve core displacement sensor signal, a dynamic compensation function is defined, and the static mapping function and dynamic compensation function are integrated and fused to form the compensated voltage drive signal, including...

[0081] Based on the reconstruction and update of the state variable vector, control voltage signal sequence data and measured flow signal data at the valve orifice are extracted to identify dead zones and saturation zones. Dead zone judgment is performed based on the lower limit of valve orifice flow detection resolution, and saturation zone judgment is performed based on the flow change rate threshold, as expressed as:

[0082] ;

[0083] ;

[0084] ;

[0085] ;

[0086] in, and These represent the positive and negative boundary voltages of the dead zone, respectively, and i represents the sequence index. Indicates being bound by, This represents the i-th value of the measured flow rate signal. This indicates the lower limit of the valve orifice flow detection resolution, obtained from the flow sensor calibration value. and These represent the positive and negative boundary voltages of the saturation region, respectively. This indicates that the flow rate Q at point i corresponds to the control voltage. The derivative of The threshold representing the rate of change of flow can be represented by... Calculation determined;

[0087] Based on the positive and negative boundary voltages of the dead zone and the saturation zone, the response interval of the valve orifice is divided as linear region data. The linear region gain is then fitted using the least squares method and expressed as:

[0088] ;

[0089] ;

[0090] in, Represents linear region data. This represents the gain in the linear region, and na represents the total number of control voltage signal sequences. This represents the mean voltage signal of the linear region data. This represents the average measured flow signal value in the linear region.

[0091] A unified static mapping function is constructed based on the linear region gain, and the dead zone and saturation zone are linearly extended and compensated, expressed as:

[0092] ;

[0093] in, Represents a static mapping function. Indicates the maximum traffic limit;

[0094] For the static mapping function, a first-order inertial dynamic compensation model is established by introducing the valve core displacement sensor signal, and discretized using the forward Euler method. The dynamic compensation function is defined as follows:

[0095] ;

[0096] ;

[0097] ;

[0098] in, This represents the mechanical time constant of the valve core, obtained from a step response test. This indicates updated valve core displacement data. This represents the dynamic compensation function. This represents the control voltage signal updated at the discrete time point k-1;

[0099] The static mapping function and the dynamic compensation function are integrated separately to form the compensated voltage drive signal, which is expressed as follows:

[0100] ;

[0101] in, The voltage drive signal representing integrated compensation serves as the ideal execution voltage command. This represents the static mapping function of the control voltage signal at the updated discrete time point k.

[0102] By reconstructing and updating based on state variable vectors, the control voltage signal and the measured flow signal at the valve port are kept in time synchronization, realizing a consistent mapping of cross-domain signals. This provides a high-precision input basis for subsequent valve port characteristic identification. By identifying the dead zone and saturation zone of the control voltage and measured flow sequence, the valve port response interval can be accurately divided in a physical sense, thereby ensuring that a stable response relationship can still be established in the nonlinear section. By identifying the dead zone with the lower limit of flow detection resolution as the criterion and the saturation zone with the flow change rate threshold as the criterion, adaptive identification of the valve port response boundary is realized. Compared with the traditional method that relies on empirical parameters, it has repeatability and measurement consistency.

[0103] By combining the dead zone and saturation zone identification results with the linear zone gain of least squares fitting, a static mapping function with continuous transition characteristics can be constructed based on the physical interval division. This eliminates the response interval discontinuity while ensuring the linearity of the valve outlet output. Through the linear extension compensation of the static mapping function, continuous response correction of the valve outlet nonlinear section is achieved, so that the control signal no longer produces abrupt changes at the boundary of the dead zone and saturation zone, thus improving the controllability and signal smoothness of the control system.

[0104] By introducing a first-order inertial dynamic compensation model based on the valve core displacement sensor signal into the static mapping function, the real-time dynamic response of the valve opening can be coordinated with the static characteristic function, achieving a unified description of static and dynamic characteristics. Through forward Euler discretization, the continuous mechanical inertial response process is transformed into a differential form that can be calculated in real time, enabling the compensation model to be embedded in the digital control system for online updates, thereby maintaining control accuracy under dynamic operating conditions.

[0105] By integrating static mapping functions and dynamic compensation functions, the compensated voltage drive signal can maintain ideal linearity in steady state and correct hysteresis errors in real time during dynamic changes. This achieves unified correction of three types of nonlinear distortions: dead zone, saturation, and hysteresis. This integrated compensation mechanism isomorphizes static structural parameters with dynamic response parameters, giving the compensation output time-domain continuity and amplitude consistency. This results in a stable voltage-flow mapping relationship across the entire control range. Through this combination, the system can maintain consistent valve flow control characteristics under different loads and oil temperatures, significantly improving the linearity and dynamic predictability of the parallel valve control system.

[0106] S3, based on the physical limitations of the controller specifications, determines the actual voltage signal sent to the servo valve driver, updates the reconstructed state variable vector, and performs state prediction;

[0107] Preferably, the actual voltage signal sent to the servo valve driver is determined based on the physical limitations of the controller specifications, including:

[0108] Based on the integrated compensated voltage drive signal, physical limits are applied according to the controller's maximum and minimum voltage specifications, and the actual voltage signal sent to the servo valve driver is determined, expressed as:

[0109] ;

[0110] in, This represents the actual voltage signal sent to the servo valve driver. This indicates the maximum voltage specified by the controller.

[0111] By introducing physical amplitude limiting constraints on the integrated compensated voltage drive signal, the control command is kept consistent with the electrical limits of the servo valve driver. This enables adaptive trimming of the control signal within the hardware's executable range, thus avoiding saturation distortion without increasing control latency. Through this constraint process, the output signal can undergo amplitude normalization before entering the servo valve, ensuring continuous and overshoot-free execution response of the control system and providing physically consistent input conditions for subsequent state prediction models.

[0112] Furthermore, the reconstructed state variable vector is updated for state prediction, including:

[0113] The reconstructed state variable vector is updated based on the voltage signal sent to the servo valve driver, and state prediction is performed through recursive calculation, as follows:

[0114] ;

[0115] in, This represents the predicted state vector at time k+i+1. The discrete state transition matrix represents the index of the (i+1)th prediction step. , This represents the actual voltage signal at step j.

[0116] By reconstructing and recursively updating the state variable vector based on the actual executed voltage signal after amplitude limiting, the model is driven by real execution results rather than ideal control signals, achieving closed-loop consistency between the prediction process and the actual physical execution process. This mechanism allows the prediction model to no longer rely on idealized assumptions, but instead constructs a dynamic mapping through real-time feedback, thereby significantly improving the physical reliability and numerical stability of the state prediction.

[0117] S4, based on the deviation between the predicted state and the desired state, outputs a predicted voltage signal;

[0118] Preferably, based on the deviation between the predicted state and the desired state, a predicted voltage signal is output, including:

[0119] Set the desired state and define the objective function. Evaluate the deviation between the predicted state and the desired state, as well as the change in the control quantity. Define constraints to minimize the objective function and output the predicted voltage signal, expressed as:

[0120] ;

[0121] ;

[0122] ;

[0123] ;

[0124] ;

[0125] Where J represents the objective function, Indicates the prediction step size. Indicates the weight of the control smoothing term. Indicates the control step size. This represents the change in the control quantity at time k+i. This represents the optimal control quantity at time k. and These represent the upper and lower limits of the control voltage, respectively. and These represent the upper and lower limits of the piston speed data, respectively. This represents the predicted voltage signal.

[0126] By introducing the desired state and defining an objective function during the prediction process, the deviation between the predicted state and the desired state is minimized, while the rate of change of the control variable is constrained, thus achieving a dynamic trade-off between state accuracy and control smoothness. The setting of the control smoothing term enables the system to maintain stable output under conditions of measurement noise and model uncertainty, avoiding mechanical oscillations of the valve core caused by rapid fluctuations in traditional model predictive control, thereby improving actuator lifespan and response consistency.

[0127] This embodiment also provides a computer device applicable to the model predictive control method for electro-hydraulic servo systems, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the model predictive control method for electro-hydraulic servo systems proposed in the above embodiment.

[0128] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0129] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the model predictive control method for an electro-hydraulic servo system as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0130] In summary, this invention, through the combined use of the force balance equation in the mechanical domain and the compensation signal in the electronic control domain, enables the voltage change issued by the controller to be equivalent to direct control of the output force. By unifying the use of the flow mapping function of the parallel valve group and the discrete state prediction model, the nonlinear characteristics of each valve port are integrated through the fusion of the static mapping function and the dynamic compensation function. This allows the compensated voltage drive signal to maintain ideal linearity in steady state and to correct hysteresis errors in real time during dynamic changes. The fusion compensation mechanism isomorphizes the static structural parameters and dynamic response parameters, giving the compensated output time-domain continuity and amplitude consistency, thereby forming a stable voltage-flow mapping relationship throughout the entire control range. Through this combination, the system can maintain consistent valve port flow control characteristics under different load and oil temperature conditions, significantly improving the linearity and dynamic predictability of the parallel valve control system.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A model predictive control method for an electro-hydraulic servo system, characterized by, The method comprises the following steps: Based on the electro-hydraulic servo system, the state variable vector is defined according to the resultant force formed by the equivalent cavity pressure difference, the forward Euler method is used for discretization processing, the piston force balance equation is constructed, the state variable vector data is updated, the relationship equation between the electro-controlled valve core opening and the control voltage is set, the flow of the hydraulic cylinder into the upper and lower cavities is updated, and the state variable vector is reconstructed and updated; The control voltage signal sequence data and the measured flow signal data of the valve port are extracted, the dead zone and the saturation zone are identified, the response interval of the valve port is divided, the unified static mapping function is constructed, the first-order inertia dynamic compensation model is established by introducing the valve core displacement sensor signal, the dynamic compensation function is defined, the static mapping function and the dynamic compensation function are integrated, and the compensated voltage driving signal is formed; According to the physical limitation of the controller specification, the voltage signal actually sent to the servo valve driver is determined, and the reconstructed state variable vector is updated for state prediction; According to the deviation between the state prediction and the expected state, the predicted voltage signal is outputted; The state variable vector is defined, the forward Euler method is used for discretization processing, the piston force balance equation is constructed, the state variable vector data is updated, the relationship equation between the electro-controlled valve core opening and the control voltage is set, the flow of the hydraulic cylinder into the upper and lower cavities is updated, and the state variable vector is reconstructed and updated, which comprises the following steps: The state variable vector is defined based on the hydraulic cylinder piston displacement data, the piston speed data and the resultant force formed by the equivalent cavity pressure difference; The pressure data of the two cavities of the hydraulic cylinder and the effective area of the hydraulic cylinder piston are collected to calculate the pressure state values of the two cavities; The forward Euler method is used for discretization processing to obtain the upper and lower cavity pressure values, and the piston force balance equation is constructed to update the piston speed, the piston acceleration and the resultant force formed by the equivalent cavity pressure difference; The relationship equation between the electro-controlled valve core opening and the control voltage is set, and the flow of the hydraulic cylinder into the upper and lower cavities is updated; The state variable vector is reconstructed and updated according to the updated flow of the hydraulic cylinder into the upper and lower cavities, the piston speed, the piston acceleration and the resultant force formed by the equivalent cavity pressure difference; The boundary values of the hydraulic cylinder piston displacement data, the piston speed data and the resultant force formed by the equivalent cavity pressure difference are based on the safety range standard of the equipment in use; The dead zone and the saturation zone are identified, the response interval of the valve port is divided, the unified static mapping function is constructed, the first-order inertia dynamic compensation model is established by introducing the valve core displacement sensor signal, the dynamic compensation function is defined, the static mapping function and the dynamic compensation function are integrated, and the compensated voltage driving signal is formed, which comprises the following steps: Based on the reconstruction and update of the state variable vector, the control voltage signal sequence data and the measured flow signal data of the valve port are extracted, the dead zone and the saturation zone are identified, the lower limit of the valve port flow detection resolution is used for dead zone judgment, and the flow rate threshold is used for saturation zone judgment; According to the positive and negative boundary voltage data of the dead zone and the saturation zone, the response interval of the valve port is divided as linear zone data, and the linear zone gain is outputted by least square fitting. A static mapping function is constructed based on a linear region gain, and a dead zone and a saturation region are linearly extended and compensated; A first-order inertia dynamic compensation model is established by introducing a valve core displacement sensor signal for the static mapping function, and is discretized by a forward Euler method, and a dynamic compensation function is defined; The static mapping function and the dynamic compensation function are integrated respectively to form a compensated voltage driving signal; The physical limit of the controller specification is determined to determine the voltage signal actually sent to the servo valve driver, including, The voltage driving signal of the integrated compensation is physically limited according to the maximum voltage and the minimum voltage of the controller specification, and the voltage signal actually sent to the servo valve driver is determined; The reconstructed state variable vector is updated to perform state prediction, including, The reconstructed state variable vector is updated based on the voltage signal sent to the servo valve driver, and state prediction is performed by recursive calculation; The deviation between the state prediction and the expected state is outputted to output the predicted voltage signal, including, The expected state is set and a target function is defined, the deviation between the predicted state and the expected state and the change of the control amount are evaluated, the constraint condition is defined to minimize the target function, and the predicted voltage signal is outputted.

2. The electro-hydraulic servo system model predictive control method of claim 1, wherein: The constraint condition is defined, including, The boundary values of the hydraulic cylinder piston displacement data, the piston speed data and the equivalent cavity pressure difference are based on the safety range standard of the equipment.

3. The electro-hydraulic servo system model predictive control method of claim 1, wherein: Data is collected based on the electro-hydraulic servo system, including, The piston displacement and piston speed data are collected for the hydraulic cylinder of the electro-hydraulic servo system, the pressure data are collected for the two cavities of the hydraulic cylinder, the input voltage of the electro-hydraulic servo valve is collected for the control signal generator, and the hydraulic pressure data are collected for the hydraulic circuit of the electro-hydraulic servo system.

4. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that: The processor executes the computer program to realize the steps of the electro-hydraulic servo system model predictive control method of any one of claims 1-3.

5. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the electro-hydraulic servo system model predictive control method of any one of claims 1-3.

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