An active control method for electro-hydraulic servo system based on finite time control

Abstract

The application provides an active control method of an electro-hydraulic servo system based on finite time control. The method dynamically restricts the error boundary through a time-varying obstacle Lyapunov function, combines a backstepping recursive control framework with a fractional order convergence term, significantly improves the convergence speed and anti-interference ability of the system, effectively suppresses the overshoot problem and chattering phenomenon of PID control, designs a feedforward compensation and an adaptive disturbance observation mechanism in view of the nonlinear characteristics and anti-interference problems of the electro-hydraulic servo system, and still can quickly recover stability under strong external disturbance, thereby ensuring the accuracy and robustness of the control force output, and based on the similarity criterion, a scale experiment platform is constructed to verify the engineering universality of the control strategy, and an efficient, reliable and easy-to-deploy solution is provided for the anti-seismic control of complex structures.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of structural engineering vibration control and mechatronic-hydraulic integration, and particularly relates to an active control method of an electro-hydraulic servo system based on finite time control, and is particularly suitable for high-rise building seismic control scenes. BACKGROUND

[0002] In the field of building structure seismic resistance, an active tuned mass damper (ATMD) can offset seismic energy by applying a control force in real time, and its performance is significantly better than that of a passive TMD system. An electro-hydraulic servo driving system has become the mainstream actuation scheme for ATMDs due to its high power density and fast response. However, the existing technology has the following bottlenecks: the valve flow nonlinearity and friction hysteresis inherent in the hydraulic system can cause overshoot oscillation of the traditional PID control; the frequency spectrum of seismic excitation is complex and variable, and although the existing sliding mode control strategy can improve robustness, high-frequency chattering can accelerate the wear of hydraulic components; the construction cost of a full-size experimental platform is high, and the existing scaling method only focuses on geometric similarity, resulting in distorted control force mapping.

[0003] Although existing research attempts to improve control performance through adaptive algorithms or traditional optimization methods such as GA, PSO, DE, etc., the convergence speed is difficult to meet the real-time requirements of seismic response, while emerging multi-objective optimization strategies and robust control methods based on Lyapunov functions provide theoretical support and practical paths for high-performance control under complex working conditions. SUMMARY

[0004] The application aims to solve the problems of low control accuracy and slow convergence speed of existing electro-hydraulic servo ATMD systems due to nonlinear characteristics, time delay effects, and insufficient disturbance rejection, and proposes an active control method of an electro-hydraulic servo system based on finite time control. The method realizes the finite time convergence and dynamic constraint of tracking error by designing a time-varying barrier Lyapunov function (TVBLF) combined with a backstepping recursive control architecture, significantly improving the robustness and control efficiency of the system under complex working conditions.

[0005] The application is implemented by the following technical solutions, and an active control method of an electro-hydraulic servo system based on finite time control is proposed, which comprises:

[0006] S1, an electro-hydraulic servo driving ATMD vibration reduction structure model is established, and the optimal control force U is determined by comparing the TMD and ATMD control strategies;

[0007] S2, the hydraulic system parameters are designed based on the optimal control force U, and an electro-hydraulic servo system mathematical model is established;

[0008] S3, design a finite-time controller based on time-varying barrier Lyapunov function, dynamically constrain the tracking error through a third-order backstepping recursive architecture, and realize overshoot suppression and finite-time convergence by combining fractional order terms;

[0009] S4, build an electro-hydraulic servo scaled experiment platform based on similarity criteria, integrate the controller for multi-condition verification, including step response, sine tracking, and force control experiment under seismic wave excitation.

[0010] Further, the S1 specifically includes:

[0011] Simplify the building structure into a multi-degree-of-freedom linear system, and establish the motion equation using Lagrange equation:

[0012]

[0013] Where X is the displacement vector of the structure relative to the ground, H is the control force action position matrix, I is the seismic wave action position matrix, M, C and K are the mass matrix, damping matrix and stiffness matrix of the ATMD control system respectively, x g is the seismic wave input vector, and U is the optimal control force.

[0014] Establish a vibration response evaluation system including inter-story drift angle indicators.

[0015] Use LQR algorithm to solve the optimal control force that minimizes the inter-story drift angle.

[0016] Further, the LQR algorithm design includes:

[0017] Construct a quadratic performance index function based on the dynamic response of the structure ;

[0018] Where the positive semi-definite matrix Q represents the structural vibration energy index, and the positive definite matrix R reflects the energy consumption parameter of the control system, which together constitute the core adjustment parameters of active control; the first term of the function quantifies the total energy of the structure vibration, and the second term represents the energy input of the control system;

[0019] Calculate the feedback gain matrix of the optimal control force ;

[0020] Where is the feedback gain matrix of the control input, which is used to calculate the optimal control force U, P is the solution of Riccati equation, and B is the input matrix of the system.

[0021] Further, the mathematical model in S2 includes:

[0022] Consider the hydraulic cylinder dynamics equation considering the servo valve flow ;

[0023] Where Ploadis the load pressure (MPa), V t Vtotais the total volume of the oil return chamber (m 3 ), Aeffis the effective area of the hydraulic cylinder piston (m 2 ), Xoutis the output displacement of the hydraulic cylinder (m), Kleakis the leakage coefficient in the system (m 3 / (s·Pa) ), Kv is the equivalent bulk modulus of the oil (MPa) ;

[0024] The load force balance equation including the leakage coefficient and the viscous friction coefficient:

[0025] ;

[0026] where M is the equivalent mass of the piston and the connected load converted to the end of the piston rod (kg), C is the viscous damping coefficient of the system (N·s / m), K is the stiffness of the elastic element in the system (N / m), F is the external load applied to the piston (N) ;

[0027] The valve port flow equation of the servo valve including the flow gain coefficient ;

[0028] The system transfer function model is obtained by solving the three equations simultaneously.

[0029] Further, the system transfer function model is:

[0030] .

[0031] Further, the design method of the finite time controller in S3 includes:

[0032] Designing a three-order backstepping recursive control architecture , constructing a time-varying barrier function to dynamically constrain the error boundary, and ensuring that the absolute value of z1 is less than this boundary; wherein , is the virtual control law; 、 、 z1, z2, and z3 represent the position tracking error, the speed tracking error, and the acceleration tracking error, respectively;

[0033] Designing a virtual control law , , combined with a fractional order term to accelerate convergence;

[0034] Deriving the actual control law The finite-time convergence of the system is proved using Lyapunov stability theory; the feedforward term of this control law... It can offset the inherent dynamics of the system, reduce the feedback gain requirement, and reduce the feedback term. Provides damping to actively suppress resonance in hydraulic systems; fractional term Forced finite-time convergence ensures that the error returns to zero within a predetermined time; compensation term. Suppress unmodeled dynamics and external disturbances.

[0035] Furthermore, in step S3, a virtual control law is designed. , Specifically:

[0036] ,

[0037] The first item The first term is the exponential convergence term, the second term is the finite-time term, and the third term is the Young's compensation term;

[0038]

[0039] Among the new items Used for active cancellation The coupling terms in.

[0040] Furthermore, the similarity criteria specifically include: a geometric scaling ratio of 1 / 36, with the prototype cylinder diameter of 0.3072m corresponding to a model cylinder diameter of 0.05m; a force scaling ratio of 1 / 36, with the maximum output force of the original system corresponding to the maximum output force of the scaled-up system being 2800N, and the load prototype being 58t corresponding to the load of the scaled-up system being 100kg.

[0041] The present invention also proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the active control method for an electro-hydraulic servo system based on finite-time control.

[0042] The present invention also proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the active control method for an electro-hydraulic servo system based on finite-time control.

[0043] The beneficial effects of this invention are:

[0044] The application fuses a finite time control algorithm with an electro-hydraulic servo active tuned mass damper (ATMD) system, dynamically restricts an error boundary through a time-varying barrier Lyapunov function, combines a backstepping recursive control architecture with a fractional order convergence term, significantly improves the convergence speed and anti-interference ability of the system, and effectively suppresses the overshoot problem and chattering phenomenon of the PID control; in view of the nonlinear characteristics and anti-interference problems of the electro-hydraulic servo system, a feedforward compensation and adaptive disturbance observation mechanism is designed, which can still quickly recover stability under strong external disturbance, and ensures the accuracy and robustness of the control force output; a scale experiment platform is constructed based on the similarity criterion, the engineering universality of the control strategy is verified, and an efficient, reliable and easy-to-deploy solution for seismic control of complex structures is provided. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only a part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on the provided drawings.

[0046] Figure 1 A flowchart of the active control method of the electro-hydraulic servo system based on finite time control of the present application;

[0047] Figure 2 A schematic diagram of the shock absorption structure model of the present application;

[0048] Figure 3 A schematic diagram of the electro-hydraulic servo valve controlled cylinder driven ATMD system of the present application;

[0049] Figure 4 A schematic diagram of the overall architecture of the finite time controller of the present application;

[0050] Figure 5 A detail view of the scale hydraulic experiment table of the present application. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0052] The existing electro-hydraulic servo ATMD system has the defects of large overshoot and difficult to eliminate steady-state error under the condition of strong nonlinearity and high-frequency disturbance. The present application adopts a three-order backstepping recursive control framework, introduces a time-varying barrier function to dynamically constrain the error boundary, accelerates the system state convergence through a fractional order convergence term, and combines feedforward compensation and disturbance observation mechanism to effectively suppress the nonlinear disturbance and time delay effect of the hydraulic system, and ensure the rapidity and stability of the control force output. When designing the control system for the actual structure, the nonlinearity of the system and the randomness of the disturbance need to be considered. Therefore, when designing the control system, the working principle of the electro-hydraulic servo system is combined to establish the mathematical model, the DE-PID control strategy is used to optimize the system, and the simulation analysis of the tracking control verifies that the system can ensure good control effect.

[0053] Specifically, in combination with Figures 1-5 The present application proposes an active control method for an electro-hydraulic servo system based on finite time control, which comprises the following steps:

[0054] S1, a model of an electro-hydraulic servo driven ATMD vibration reduction structure is established, and the optimal control force U is determined by comparing the TMD and ATMD control strategies;

[0055] The S1 specifically comprises:

[0056] The building structure is simplified as a multi-degree-of-freedom linear system, and the motion equation is established by using Lagrange equation:

[0057] ;

[0058] Wherein X is the displacement vector of the structure relative to the ground, H is the control force action position matrix, I is the seismic wave action position matrix, M, C and K are the mass matrix, damping matrix and stiffness matrix of the ATMD control system respectively, x g is the seismic wave input vector, and U is the optimal control force;

[0059] A vibration response evaluation system including inter-story drift angle index is established;

[0060] The LQR algorithm is used to solve the optimal control force for minimizing the inter-story drift angle, specifically, the seismic wave (ElCentro wave, Taft wave, etc.) excitation simulation is performed to obtain the displacement response curve of each floor, and the LQR algorithm is used to calculate the optimal control force, which provides a basis for the output force design of the electro-hydraulic servo system.

[0061] The LQR algorithm design comprises:

[0062] A quadratic performance index function based on the dynamic response of the structure is constructed ;

[0063] Wherein the positive semi-definite matrix Q represents the structure vibration energy index, the positive definite matrix R reflects the energy consumption parameter of the control system, and the two together constitute the core adjustment parameters of active control; the first term of the function quantifies the total energy of structure vibration, and the second term represents the energy input of the control system;

[0064] Feedback gain matrix of optimal control force ;

[0065] Wherein is the feedback gain matrix of control input, which is used to calculate the optimal control force U, P is the solution of Riccati equation, and B is the input matrix of the system.

[0066] S2, based on the optimal control force U, design the hydraulic system parameters, and establish the mathematical model of electro-hydraulic servo system;

[0067] The mathematical model in S2 includes:

[0068] Hydraulic cylinder dynamics equation considering servo valve flow ;

[0069] Wherein is the load pressure (MPa), V t is the sum of the oil inlet and return cavity volume (m 3 ), is the effective action area of the hydraulic cylinder piston (m 2 ), is the output displacement of the hydraulic cylinder (m), is the leakage coefficient of the system (m 3 / (s·Pa)), is the equivalent bulk modulus of oil (MPa);

[0070] Load force balance equation containing leakage coefficient and viscous friction coefficient:

[0071] ;

[0072] Wherein is the equivalent mass of the piston and the connected load converted to the piston rod end (kg), is the viscous damping coefficient of the system (N·s / m), is the stiffness of the elastic element in the system (N / m), is the external load applied to the piston (N);

[0073] Valve port flow equation of servo valve containing flow gain coefficient ;

[0074] The transfer function model of the system is obtained by simultaneously solving the three equations.

[0075] The system transfer function model is:

[0076] .

[0077] The PID parameters are optimized by using a differential evolution algorithm (DE), and a target function is: By population size M=50 and iteration number G=100, the optimal PID parameters Kp=10000, Ki=0.2 and Kd=150 are obtained.

[0078] In step S3, a finite time controller based on a time-varying barrier Lyapunov function is designed, the tracking error is dynamically constrained through a three-order backstepping recursive structure, and overshoot suppression and finite time convergence are realized by combining a fractional order term.

[0079] The design method of the finite time controller in step S3 includes:

[0080] A three-order backstepping control structure is designed , a time-varying barrier function is constructed to dynamically constrain the error boundary, and it is ensured that the absolute value of z1 is less than the boundary; wherein , is a virtual control law, which is designed step by step through backstepping; 、 、 represent the position tracking error, the speed tracking error and the acceleration tracking error respectively;

[0081] The virtual control law is designed , , and a fractional order term is combined to accelerate convergence;

[0082] The actual control law is derived , and the finite time convergence of the system is proved by Lyapunov stability theory; the feedforward term of the control law can offset the inherent dynamics of the system, reduce the feedback gain requirement, and the feedback term provides damping active suppression of hydraulic system resonance; the fractional order term forces finite time convergence and ensures that the error is zero within a predetermined time; and the compensation term suppresses unmodeled dynamics and external disturbances.

[0083] In step S3, the virtual control law is designed , Specifically:

[0084] ,

[0085] The first term is an exponential convergence term, the second term is a finite time term, and the third term is a Yang compensation term.

[0086]

[0087] wherein the new term is used to actively cancel the coupling term.

[0088] S4, an electro-hydraulic servo scaled-down experiment platform based on similarity criteria is built, and a controller is integrated to verify multiple working conditions, including step response, sine tracking, and force control experiment under seismic wave excitation.

[0089] The similarity criteria specifically include: geometric scaling ratio of 1 / 36, prototype cylinder diameter of 0.3072 m corresponding to model cylinder diameter of 0.05 m; force scaling ratio of 1 / 36, prototype maximum output force corresponding to scaled-down system maximum output force of 2800 N, and load prototype of 58 t corresponding to scaled-down system load of 100 kg.

[0090] The design method of the scaled-down experiment platform in S4 includes:

[0091] Based on the Cauchy number similarity criterion, the hydraulic cylinder diameter (prototype 307.2 mm→model 50 mm) and the load mass (prototype 58 t→model 100 kg) are scaled down in proportion;

[0092] The quantitative indicators include mean square error (MSE), mean absolute error (MAE), determination coefficient (R²), and overshoot, to verify the engineering effectiveness.

[0093] The specifications of the scaled-down hydraulic experiment table of the S4 step include:

[0094] Hydraulic cylinder: rated pressure 20 MPa; cylinder diameter 50 mm; rod diameter 23 mm; effective stroke 400 mm;

[0095] Electro-hydraulic servo valve: RT6615E series four-way two-stage servo valve with spool and valve sleeve;

[0096] Translational load: maximum hanging weight 250 kg; maximum allowable force 5000 N;

[0097] Hydraulic pump: SYDFEE type, maximum displacement 28 mL;

[0098] Control system: SINAMICS S120 AC drive control system;

[0099] Data acquisition module: NI USB M series, 16 channels.

[0100] Embodiment

[0101] The present application proposes a structure active control method based on a finite time controller controlling an electro-hydraulic servo system drive, which comprises the following steps:

[0102] (1) Establish an electro-hydraulic servo-driven ATMD vibration reduction structure model, and determine the optimal control force U by comparing the control strategies of TMD and ATMD;

[0103] (2) Design the hydraulic system parameters based on the optimal control force U, and establish a mathematical model of the electro-hydraulic servo system;

[0104] (3) Design a finite time controller based on a time-varying barrier Lyapunov function, dynamically constrain the tracking error through a three-order backstepping recursive architecture, and realize overshoot suppression and finite time convergence in combination with a fractional order term;

[0105] (4) Build an electro-hydraulic servo scaled-down experimental platform based on the similarity theory, integrate the controller, and verify it under multiple working conditions, including step response, sine tracking, and force control experiments under seismic wave excitation.

[0106] As a preferred embodiment of the present application, in step (1), the process of determining the optimal control force is as follows:

[0107] (1-1) Simplify the building structure into a multi-degree-of-freedom linear system, and establish the motion equation using the Lagrange equation:

[0108]

[0109] Wherein, M is the mass matrix, C is the damping matrix, K is the stiffness matrix, and H is the control force action position matrix.

[0110] (1-2) Calculate the optimal control force using the LQR algorithm;

[0111] (1-3) Input the building structure mass and stiffness parameters into the control system to generate an initial state space model.

[0112] (1-4) Select El Centro wave, Taft wave, and other seismic excitations as external excitations, and adjust the amplitude to 0.2 times the gravitational acceleration.

[0113] (1-5) Start the real-time control program, monitor the top layer displacement, control force output, and system energy consumption.

[0114] As a preferred embodiment of the present application, with reference to Figure 3 , in step (2), establishing the mathematical model of the electro-hydraulic servo system includes the following steps:

[0115] (2-1) System dynamic model establishment: considering the servo valve flow, hydraulic cylinder leakage, and oil compressibility, a relationship model of hydraulic cylinder output displacement and valve core control signal is established; in combination with the equivalent mass of the piston, viscous damping, and external load, the load dynamic characteristics are described; a linear relationship model of valve core displacement and flow output is established.

[0116] (2-2) Differential evolution algorithm (DE) is used to optimize the PID control parameters, the population size is set to 50, the iteration number is set to 100, and the integral time absolute error (ITAE) is considered as the target function to obtain the optimal parameter combination.

[0117] (2-3) After determining the PID parameters, the model is stimulated and tested in the Simulink platform. The test signals include step, sine and ramp signals to comprehensively evaluate the dynamic response characteristics of the model.

[0118] As a preferred embodiment of the application, with reference to Figure 4 , in step (3), designing a finite time controller based on a time-varying barrier Lyapunov function comprises the following steps:

[0119] (3-1) Defining the tracking error, taking the difference between the target displacement and the actual displacement as the error variable z1, and expanding it to high-order errors z2, z3;

[0120] (3-2) Constructing an exponential decay type error boundary function to ensure that the error is always within a safe range.

[0121] (3-3) Designing a backstepping recursive control law, designing a virtual control law layer by layer, and combining a fractional order term to accelerate convergence.

[0122] (3-4) Building a high-precision electro-hydraulic servo system simulation platform in the Simulink environment, verifying the performance of the controller in time-varying tracking and disturbance suppression through modular packaging, parameterized configuration and dynamic response testing, and providing data support for actual system debugging.

[0123] As a preferred embodiment of the application, with reference to Figure 5 , in step (4), building an electro-hydraulic servo scaled-down experimental platform based on similarity criteria comprises the following steps:

[0124] (4-1) Similarity criteria and parameter design, the geometric scale ratio is set to 1:6, the force scale ratio is set to 1:36, the pressure of the prototype and the model is kept consistent (15MPa), the cylinder diameter is reduced to 50mm, and the load mass is adjusted to 100kg.

[0125] (4-2) Hardware integration and control deployment, the hydraulic cylinder and the servo valve are connected through a rigid pipeline, and the load is simulated by a counterweight block to simulate the actual mass; deploy a force sensor, develop a real-time control program based on the LabVIEW platform, and embed the finite time control algorithm.

[0126] (4-3) Test procedure and verification index, input step signal, record displacement response curve, evaluate overshoot and regulation time; input 0.5Hz sinusoidal signal, calculate mean square error (MSE) and determination coefficient (R2); load El Centro, Taft wave optimal control force data, compare control force output and target curve.

[0127] The application further provides an electronic device, including a memory and a processor, the memory stores a computer program, and the processor realizes the steps of the active control method of the electro-hydraulic servo system based on finite time control when executing the computer program.

[0128] The application further provides a computer readable storage medium for storing computer instructions, and the computer instructions realize the steps of the active control method of the electro-hydraulic servo system based on finite time control when executed by a processor.

[0129] The memory in the embodiments of the application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. The non-volatile memory can be a read only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (EPROM), an electrically EPROM (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example, and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM). It is to be noted that the memory of the method described in the application is intended to include, but not be limited to, these and any other suitable types of memory.

[0130] In the above embodiments, all or part of the methods can be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the methods can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through a wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that includes one or more available media sets. The available media can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a high-density digital video disc (DVD)), or a semiconductor medium (such as a solid state disc (SSD)), etc.

[0131] In the implementation process, each step of the above method can be completed by integrated logic circuit of hardware in the processor or instruction in the form of software. The steps of the method disclosed in the embodiments of the present application can be directly embodied as hardware processor execution completion, or executed by hardware and software modules in the processor. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, or other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method. To avoid repetition, it will not be described in detail here.

[0132] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with a signal processing capability. In the implementation process, each step of the method embodiments can be completed by the integrated logic circuit of hardware in the processor or the instructions in the form of software. The processor mentioned above can be a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and combines the hardware to complete the steps of the above method.

[0133] The above describes in detail the active control method of the electro-hydraulic servo system based on finite time control. The principle and implementation of the present application are described by using specific examples. The above description of the embodiments is only used to help understand the method of the present application and its core idea. For those skilled in the art, according to the idea of the present application, the specific implementation and application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A finite time control based active control method for electro-hydraulic servo system, characterized in that, The method comprises: S1, an electro-hydraulic servo-driven ATMD vibration reduction structure model is established, and optimal control force U is determined by comparing TMD and ATMD control strategies; S2, a hydraulic system parameter is designed based on the optimal control force U, and a mathematical model of an electro-hydraulic servo system is established; S3, a finite time controller based on a time-varying barrier Lyapunov function is designed, a tracking error is dynamically constrained through a three-order backstepping recursive architecture, and overshoot suppression and finite time convergence are realized in combination with a fractional order term; S4, an electro-hydraulic servo scaled-down experiment platform based on a similarity criterion is built, and a controller is integrated to perform multi-condition verification, including force control experiments under step response, sine tracking and seismic wave excitation; The design method of the finite time controller in S3 comprises: Designing a three-step recursive backstepping control architecture , constructing a time-varying barrier function to dynamically constrain the error boundary, ensuring that the absolute value of z1 is less than this boundary; wherein , is a virtual control law; , , respectively represent the position tracking error, the speed tracking error, and the acceleration tracking error; Designing virtual control laws , , incorporating fractional order terms to accelerate convergence; Deduce actual control law Prove finite time convergence of system by Lyapunov stability theory; Feedforward term of control law Can offset inherent dynamics of system, reduce demand of feedback gain; Feedback term Provide damping active suppression of resonance of hydraulic system; Fractional order term Force finite time convergence, ensure error to be zero in predetermined time; Compensation term Suppress unmodeled dynamics and external disturbance.

2. The method of claim 1, wherein, The S1 specifically comprises: A building structure is simplified as a multi-degree-of-freedom linear system, and a motion equation is established by using Lagrange equation: where X is the displacement vector of the structure relative to the ground, H is the control force location matrix, I is the seismic wave location matrix, M, C and K are the mass matrix, damping matrix and stiffness matrix of the ATMD control system, respectively, x g is the seismic wave input vector, and U is the optimal control force. A vibration response evaluation system including a story drift angle index is established; An LQR algorithm is used to solve optimal control force minimizing the story drift angle.

3. The method of claim 2, wherein, The LQR algorithm design comprises: Constructing a quadratic performance index function based on structural dynamic response ; Wherein, a semi-positive definite matrix Q represents a structure vibration energy index, and a positive definite matrix R reflects a control system energy consumption parameter, and both of them together constitute core adjustment parameters of active control; the first term of the function quantifies the total energy of structure vibration, and the second term represents the energy input of the control system; Computing feedback gain matrix for optimal control forces ; wherein P is the feedback gain matrix for the control input, which is used to calculate the optimal control force U, P is the solution of the Riccati equation, and B is the input matrix of the system.

4. The method of claim 3, wherein, The mathematical model in S2 comprises: Hydraulic cylinder dynamics equation considering servo valve flow ; wherein P is the load pressure (MPa), V t V is the sum of the oil inlet and return chamber volumes (m 3 ), A is the effective action area of the hydraulic cylinder piston (m 2 ), X is the output displacement of the hydraulic cylinder (m), K is the leakage coefficient in the system (m 3 / (s·Pa)), E is the equivalent bulk modulus of the oil (MPa); A load force balance equation including a leakage coefficient and a viscous friction coefficient: ； wherein is the mass (kg) of the piston and equivalent conversion of connected loads to the end of the piston rod, is the viscous damping coefficient (N·s / m) of the system, is the stiffness (N / m) of the elastic element in the system, is the external load (N) applied on the piston; Valve port flow equation for a servo valve including a flow gain coefficient ; A system transfer function model is obtained by simultaneously solving the three equations.

5. The method of claim 4, wherein, In step S3, a virtual control law is designed , Specifically: ， where the first term is an exponentially converging term, the second term is a finite-time term, and the third term is a Yang's compensation term; wherein the new term for actively canceling the coupling term in 6. The method of claim 1, wherein, The similarity criterion specifically comprises: geometric scaling 1 / 36, prototype cylinder diameter 0.3072 m corresponding to model cylinder diameter 0.05 m; force scaling 1 / 36, maximum output force of the original system corresponding to maximum output force of the scaled system is 2800 N, and load prototype is 58 t corresponding to scaled system load is 100 kg. 7.An electronic device comprising a memory and a processor, the memory storing a computer program, wherein, The processor executes the computer program to realize the steps of the method in any one of claims 1-6.

8. A computer readable storage medium for storing computer instructions, characterized in that, The computer instructions are executed by the processor to realize the steps of the method in any one of claims 1-6.

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