Electro-hydraulic servo system high-frequency displacement and output force control method

Abstract

This invention relates to the field of electro-hydraulic control technology, specifically to a method for high-frequency displacement and output force control of an electro-hydraulic servo system. The method includes: S1: constructing an electro-hydraulic servo high-frequency system; S2: based on the electro-hydraulic servo high-frequency system, constructing an electro-hydraulic servo high-frequency displacement control model and an electro-hydraulic servo high-frequency output force control model to obtain continuous displacement control quantities and continuous output force control quantities; S3: based on a dual-input single-output fuzzy control model with a correction factor, integrating the continuous displacement control quantities and continuous output force control quantities, adjusting the displacement control and output force control to a continuously switching state, and continuously controlling the mechanical load module. This patent achieves high-frequency, high-precision coordinated control of displacement and output force through the construction of the electro-hydraulic servo high-frequency displacement control model and the electro-hydraulic servo high-frequency output force control model, improving response bandwidth and position tracking accuracy. Furthermore, through the coordination of the fuzzy control model, it achieves continuous and smooth switching of displacement and output force, expanding application potential.

Description

Technical Field

[0001] This invention relates to the field of electro-hydraulic control technology, specifically to a method for controlling high-frequency displacement and output force in an electro-hydraulic servo system. Background Technology

[0002] With its advantages of high power density, fast response speed and high control precision, electro-hydraulic servo system has become the core execution unit in high-end equipment manufacturing, aerospace and other fields. Its control performance directly determines the overall machine's operating accuracy and stability.

[0003] Existing electro-hydraulic servo systems typically employ a single control mode, focusing on either displacement tracking accuracy or output force stability. They lack coordinated optimization of displacement and output force under high-dynamic conditions, making it difficult for existing systems to achieve high-precision coordinated control of displacement and output force under high-frequency excitation. When simultaneously satisfying accurate trajectory tracking and constant dynamic load output in high-speed reciprocating motion, existing technologies exhibit significant limitations, often manifesting as displacement tracking lag, output force overshoot, or continuous oscillation, severely restricting the system's performance in complex and precision operations.

[0004] In addition, existing electro-hydraulic servo systems have significant limitations on the adjustment of control bandwidth. They are prone to response lag and oscillation under high-frequency conditions, which cannot meet the requirements of high-frequency displacement tracking. Furthermore, their nonlinearity and disturbance suppression capabilities are weak, making it difficult to accurately compensate for the inherent nonlinear factors of electro-hydraulic servo systems. This results in a decrease in control accuracy during dynamic processes, limiting their application potential in scenarios with higher performance requirements. Summary of the Invention

[0005] Given the lack of coordinated optimization of displacement and output force under high dynamic conditions in existing technologies, which makes it difficult for existing electro-hydraulic servo systems to achieve coordinated high-precision control of displacement and output force under high-frequency excitation, this invention provides a high-frequency displacement and output force control method for electro-hydraulic servo systems. By constructing an electro-hydraulic servo high-frequency system, the electro-hydraulic servo high-frequency displacement control model and the electro-hydraulic servo high-frequency output force control model can simultaneously take into account displacement tracking and output force stability under high dynamic conditions. This enables precise and adaptive multi-objective control of the mechanical load module, improves response bandwidth and position tracking accuracy, and ensures the trajectory accuracy and stability of the mechanical load module in high-speed reciprocating motion.

[0006] This invention provides a method for controlling high-frequency displacement and output force in an electro-hydraulic servo system, comprising:

[0007] S1: Construct an electro-hydraulic servo high-frequency system, the electro-hydraulic servo high-frequency system including: a hydraulic oil tank, a hydraulic pump connected to the hydraulic oil tank via a hydraulic circuit, an electric motor for driving the hydraulic pump, several hydraulic cylinders connected to the hydraulic oil tank via a hydraulic circuit, a solenoid valve group set on the main oil inlet line for reversing connection, an overflow valve installed on the main oil inlet line, a sensor unit for real-time signal acquisition, and a mechanical load module, wherein the several hydraulic cylinders are used to control the operation of the mechanical load module.

[0008] S2: Based on the electro-hydraulic servo high-frequency system, construct an electro-hydraulic servo high-frequency displacement control model and an electro-hydraulic servo high-frequency output force control model, and obtain continuous displacement control quantity and continuous output force control quantity.

[0009] S3: A dual-input single-output fuzzy control model based on a correction factor integrates continuous displacement control and continuous output force control, adjusts displacement control and output force control to a continuously switching state, and continuously controls the mechanical load module.

[0010] Furthermore, the mechanical load module includes a horizontal excitation unit and a vertical loading unit. Both the horizontal excitation unit and the vertical loading unit include a mass block installed at the end of the hydraulic cylinder piston rod, a damper installed on the mass block, and an elastic element sleeved on the outside of the damper. The extension and retraction of the hydraulic cylinder piston rod controls the extension and retraction of the damper.

[0011] Furthermore, the electro-hydraulic servo high-frequency displacement control model includes:

[0012] A three-state control unit is constructed to obtain real-time feedback signals of the three states, and the damping ratio of the mechanical load module is controlled in a comprehensive manner to obtain the deviation signal;

[0013] Construct a BP neural network sliding mode control unit;

[0014] The deviation signal is learned in real time through a learning algorithm, and the parameters of the mechanical load module are optimized in real time.

[0015] The continuous displacement control quantity is obtained through comprehensive calculation.

[0016] Furthermore, the construction of the three-state control unit and the acquisition of real-time feedback signals for the three states include:

[0017] Set up a feedforward stage and a feedback stage, and obtain the feedback coefficients based on the open-loop transfer function formula;

[0018] The expected closed-loop transfer function of the feedforward stage is obtained by comprehensively using the feedback coefficients.

[0019] By setting the value of the feedforward transfer function to be equal to the value of the open-loop transfer function, the near-imaginary poles in the closed-loop transfer function are eliminated, thereby expanding the bandwidth and obtaining the real-time feedback signal in three states.

[0020] Furthermore, the construction of the BP neural network sliding mode control unit includes:

[0021] Set up a three-layer output mode consisting of an input layer, a hidden layer, and an output layer; and set the input value, the actual output value, and the deviation value.

[0022] Initialize the connection weights between the hidden layer and the output layer to random numbers in the range of [-1~1];

[0023] The hyperbolic tangent function is used to calculate the input values ​​of the hidden layer, and the non-negative hyperbolic tangent function is used to calculate the input values ​​of the output layer, finally obtaining the output values ​​of the output layer;

[0024] The parameters of the real-time BP neural network are calculated by acquiring signals in real time, and the sliding mode control value is obtained by combining the sliding mode control formula.

[0025] Based on the negative gradient rule, the connection weights between the output layer and the hidden layer are adjusted in real time by combining the sliding mode control value, learning rate and momentum factor, and the real-time performance index function is obtained.

[0026] Furthermore, the electro-hydraulic servo high-frequency output force control model includes:

[0027] Establish a spatial prediction unit for electro-hydraulic servo output force;

[0028] The constraints for controlling the mechanical load module are obtained through comprehensive calculation using the cost function unit.

[0029] The continuous output force control quantity is obtained by comprehensively applying the quadratic programming formula and constraints.

[0030] Furthermore, the electro-hydraulic servo output force spatial prediction unit includes:

[0031] The basic equations of a valve-controlled symmetrical cylinder are subjected to Laplace transform and simplification to obtain a single-input single-output difference equation.

[0032] By setting the sampling time and constructing the spatial prediction characteristics of the electro-hydraulic servo output force in the prediction time domain through a single-input single-output difference equation, a sampling time is set.

[0033] Furthermore, the step of comprehensively calculating and obtaining the constraints for controlling the mechanical load module through the cost function unit includes:

[0034] The cost function formula is designed with the goal of minimizing the deviation between the system variables and the desired variables and the sum of the input signal amplitudes. A weight matrix is ​​introduced to simplify the function error in the cost function formula.

[0035] The valve core displacement of the solenoid valve assembly and the axial force output by the hydraulic cylinder are set as constraints, and the constraints are obtained through the cost function formula.

[0036] Furthermore, fuzzy control models include:

[0037] The sensor unit acquires vibration displacement signals and outputs force signals;

[0038] The vibration frequency is calculated, and the displacement signal and output force signal are linearly normalized to obtain the displacement and output force in the range of [0,1].

[0039] The displacement and output force are fuzzified into 5 fuzzy sets by a two-dimensional fuzzy control with dual input and single output, and a fuzzy rule base is established based on the correspondence between displacement and output axial force.

[0040] Using the triangular membership function, the fuzzy inference outputs a control correction factor in the range [0,1].

[0041] By using a fusion formula, displacement and output force are fused and adjusted to obtain displacement and output force in continuously switching states.

[0042] Furthermore, the fusion formula is as follows: Where α represents the control correction factor, u disp Indicates the displacement input, u force This indicates the amount of output force input.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] This invention patent achieves high-frequency, high-precision coordinated control of displacement and output force through the construction of electro-hydraulic servo high-frequency displacement control and electro-hydraulic servo high-frequency output force control models. Specifically, by constructing an electro-hydraulic servo high-frequency system, the electro-hydraulic servo high-frequency displacement control model and the electro-hydraulic servo high-frequency output force control model simultaneously consider displacement tracking and output force stability under high dynamic conditions. This enables precise and adaptive multi-objective control of the mechanical load module, improves response bandwidth and position tracking accuracy, ensures the trajectory accuracy and stability of the mechanical load module in high-speed reciprocating motion, and further enhances the output force adjustment capability and anti-interference ability under dynamic loads. Through the coordination of fuzzy control models, continuous and smooth switching of displacement and output force is achieved, maintaining excellent control performance and robustness under high-speed, high-load, and sudden change conditions. This further expands the application potential of electro-hydraulic servo systems in fields such as precision vibration simulation, high-performance fatigue testing, and advanced equipment manufacturing.

[0045] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0046] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0047] Figure 1 This is a flowchart of a high-frequency displacement and output force control method for an electro-hydraulic servo system.

[0048] Figure 2 This is a schematic diagram of an electro-hydraulic servo system.

[0049] Figure 3 This is a flowchart of the actual electro-hydraulic servo system.

[0050] Figure 4 This is a block diagram of an electro-hydraulic servo system.

[0051] Figure 5 This is a flowchart of an electro-hydraulic servo high-frequency displacement control model.

[0052] Figure 6 This is a flowchart of an electro-hydraulic servo high-frequency displacement control model.

[0053] Figure 7 This is the control flowchart for the three-state control unit.

[0054] Figure 8 This is a diagram of the BP neural network structure.

[0055] Figure 9 This is a flowchart of the electro-hydraulic servo high-frequency output force control model.

[0056] Figure 10 This is a control flowchart for a fuzzy control model.

[0057] Figure 11 Flowchart for switching between output force and displacement control. Detailed Implementation

[0058] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0059] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly set on the other component; when a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to the other component.

[0060] It should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0061] Please refer to Figures 1-11 This invention provides a method for controlling high-frequency displacement and output force in an electro-hydraulic servo system, comprising:

[0062] S1: Construct an electro-hydraulic servo high-frequency system, which includes: a hydraulic oil tank, a hydraulic pump connected to the hydraulic oil tank's hydraulic circuit, an electric motor for driving the hydraulic pump, several hydraulic cylinders connected to the hydraulic oil tank's hydraulic circuit, a solenoid valve group installed on the main oil inlet line for reversing connection, an overflow valve installed on the main oil inlet line, a sensor unit for real-time signal acquisition, and a mechanical load module. Several hydraulic cylinders are used to control the operation of the mechanical load module.

[0063] S2: Based on the electro-hydraulic servo high-frequency system, construct the electro-hydraulic servo high-frequency displacement control model and the electro-hydraulic servo high-frequency output force control model to obtain the continuous displacement control quantity and the continuous output force control quantity.

[0064] S3: A dual-input single-output fuzzy control model based on a correction factor integrates continuous displacement control and continuous output force control, adjusting displacement control and output force control to a continuous switching state to continuously control the mechanical load module.

[0065] This embodiment achieves high-frequency, high-precision coordinated control of displacement and output force by constructing an electro-hydraulic servo high-frequency displacement control model and an electro-hydraulic servo high-frequency output force control model. Specifically, by constructing an electro-hydraulic servo high-frequency system, the electro-hydraulic servo high-frequency displacement control model and the electro-hydraulic servo high-frequency output force control model simultaneously consider displacement tracking and output force stability under high dynamic conditions. This enables precise and adaptive multi-objective control of the mechanical load module, improves response bandwidth and position tracking accuracy, ensures the trajectory accuracy and stability of the mechanical load module in high-speed reciprocating motion, and further enhances the output force adjustment capability and anti-interference ability under dynamic loads. Through the coordination of fuzzy control models, continuous and smooth switching of displacement and output force is achieved, enabling excellent control performance and robustness under high-speed, high-load, and sudden change conditions. This further expands the application potential of electro-hydraulic servo systems in fields such as precision vibration simulation, high-performance fatigue testing, and advanced equipment manufacturing.

[0066] In this embodiment, as Figures 1-4 As shown, by coordinating the control of displacement and output force, the comprehensive control performance of the electro-hydraulic servo system under high-frequency dynamic conditions is improved. This enables displacement tracking and output force adjustment to adapt to rapidly changing loads and commands simultaneously, reducing overshoot and oscillation. It further enhances the continuous adaptability of the electro-hydraulic servo system to complex tasks, effectively controlling the end effector force while ensuring positioning accuracy. This expands the application scenarios and makes it suitable for advanced industrial scenarios such as high-precision assembly and force-position coordination operations, improving the stability and accuracy of the control process.

[0067] The mechanical load module includes a horizontal excitation unit and a vertical loading unit. Both the horizontal excitation unit and the vertical loading unit include: a mass block mounted on the end of the hydraulic cylinder piston rod, a damper mounted on the mass block, and an elastic element sleeved outside the damper; the extension and retraction of the hydraulic cylinder piston rod controls the extension and retraction of the damper.

[0068] In this embodiment, when the piston rod of the hydraulic cylinder extends, it pushes the piston core of the mass block and the fixed damper to move synchronously, so that the hydraulic oil inside the damper flows through the narrow throttle orifice and generates damping force. At the same time, the elastic element sleeved on the outside of the damper is compressed accordingly, generating an elastic reaction force proportional to the amount of compression.

[0069] Furthermore, the mechanical load module provides the electro-hydraulic servo high-frequency system with a precise, stable, and repeatable dynamic load, which can flexibly adapt to various complex working conditions ranging from rigid impact to flexible oscillation, further ensuring the reliability of the electro-hydraulic servo high-frequency system.

[0070] like Figures 5-8 As shown, the electro-hydraulic servo high-frequency displacement control model includes:

[0071] A three-state control unit is constructed to obtain real-time feedback signals of the three states, and the damping ratio of the mechanical load module is controlled in a comprehensive manner to obtain the deviation signal.

[0072] Construct a BP neural network sliding mode control unit.

[0073] The algorithm learns deviation signals in real time and optimizes the parameters of the mechanical load module in real time.

[0074] The continuous displacement control quantity is obtained through comprehensive calculation.

[0075] In this embodiment, the three-state control unit can increase the damping ratio of the electro-hydraulic servo system by optimizing the feedback coefficient, thereby improving the stability margin and preventing system instability under high-frequency vibration. It can also stably extend the system bandwidth, enabling the electro-hydraulic servo system to perform high-precision tracking under high-frequency operating conditions. This further enables the mechanical control module to perform synchronous high-frequency control of displacement and output force. The BP neural network sliding mode control unit can dynamically optimize the parameters of the mechanical load module in real time by using the real-time sampling and adaptive learning deviation signal of the sensor unit. This allows the electro-hydraulic servo system to adapt to complex operating condition changes, further improving the accuracy of displacement control and the robustness of the electro-hydraulic servo system.

[0076] To further explain, the construction of a three-state control unit and the acquisition of real-time feedback signals for the three states include:

[0077] Set up a feedforward stage and a feedback stage, and obtain the feedback coefficients based on the open-loop transfer function formula.

[0078] The expected closed-loop transfer function of the feedforward stage is obtained by comprehensively using the feedback coefficients.

[0079] By setting the value of the feedforward transfer function to be equal to the value of the open-loop transfer function, the near-imaginary poles in the closed-loop transfer function are eliminated, thereby expanding the bandwidth and obtaining the real-time feedback signal in three states.

[0080] The open-loop transfer function formula is:

[0081] , where ω h ξ represents the natural frequency of the electro-hydraulic servo system. h K represents the damping ratio of the mechanical load module. v Let represent the open-loop gain of the electro-hydraulic servo system, and s represent the Laplace operator.

[0082] The desired closed-loop transfer function is obtained through three-loop feedback regulation. The formula for the desired closed-loop transfer function is:

[0083] , where ω r ω is the frequency corresponding to the bandwidth of the electro-hydraulic servo system. nc ξ represents the system frequency, with a value ranging from 1.05 to 1.2 times; nc This indicates the damping ratio of the mechanical load module, with a value of 0.7.

[0084] The feedback phase setting is used to obtain three coefficient values ​​for the feedback phase: direct-axis feedback gain coefficient, excitation feedback gain coefficient, and quadrature-axis feedback gain coefficient. The calculation formula is as follows:

[0085] , where K dfK represents the direct-axis feedback gain coefficient. vf K represents the excitation feedback gain coefficient. qf This represents the cross-axis feedback gain coefficient.

[0086] The transfer function formula for the feedforward stage is: ;

[0087] The feedforward transfer function H(s) is set to be equal to the open-loop transfer function to cancel near-imaginary axis poles and thus extend the system bandwidth. The formula is as follows: ;

[0088] The three parameter values ​​obtained from this are:

[0089] .

[0090] The three-state feedback unit solves the problems of large tracking error, slow control response, limited bandwidth of control system and insufficient damping in electro-hydraulic servo system under high-frequency conditions, realizes accurate and stable control of electro-hydraulic servo system under high-frequency conditions, and further enhances the robustness of electro-hydraulic servo system.

[0091] To further explain, the construction of the BP neural network sliding mode control unit includes:

[0092] Set up a three-layer output mode consisting of an input layer, a hidden layer, and an output layer, and set the input value, the actual output value, and the deviation value.

[0093] The connection weights between the hidden layer and the output layer are initialized to random numbers in the range of [-1 to 1].

[0094] The hyperbolic tangent function is used to calculate the input values ​​of the hidden layer, and the non-negative hyperbolic tangent function is used to calculate the input values ​​of the output layer, finally obtaining the output values ​​of the output layer.

[0095] By acquiring signals in real time, the parameters of the real-time BP neural network are calculated, and the sliding mode control value is obtained by combining the sliding mode control formula.

[0096] Based on the negative gradient rule, the connection weights between the output layer and the hidden layer are adjusted in real time by combining the sliding mode control value, learning rate and momentum factor, and the real-time performance index function is obtained.

[0097] Sliding mode control enables closed-loop feedback control, and through the combination of BP neural network and learning algorithm, it can output stable and accurate real-time performance index functions.

[0098] First, the structure of the BP neural network needs to be set. By reasonably setting the number of input layer nodes I, the number of output layer nodes O, and the number of hidden layers H, and ensuring that the values ​​of each node are relatively small, it is easy to compress the scale of the electro-hydraulic servo system, thereby reducing the complexity of the electro-hydraulic servo system and shortening the training time.

[0099] The BP neural network adopts a 3-8-3 structure, that is, the input layer is set to 3 nodes, the hidden layer is set to 8 nodes, and the output layer is set to 3 nodes; the input layer takes the electro-hydraulic servo system set value, the actual output value, and the deviation value as input values.

[0100] Setting the hidden layer to eight nodes allows for efficient extraction of feature information from the input signal, balancing feature extraction capability with computational efficiency. The output layer is set to three nodes, corresponding to the three control parameters in sliding mode control: the sliding surface coefficient, the reaching law coefficient, and the switching term gain coefficient.

[0101] To ensure the randomness and diversity of the initial state of the BP neural network, the connection weights between the hidden layer and the output layer are initialized, and random numbers in the range of [-1~1] are selected for the initialization of the connection weights.

[0102] The hyperbolic tangent function is selected as the activation function of the hidden layer to ensure that the output value has zero mean and reduce offset accumulation. A non-negative hyperbolic tangent function is selected as the activation function of the output layer to ensure that the output value is non-negative, further ensuring that the output parameters can be applied to sliding mode control and guaranteeing the physical rationality of the parameters.

[0103] The formula for the hyperbolic tangent function is: ;

[0104] Its derivative formula is: .

[0105] The formula for the nonnegative hyperbolic tangent function is: ;

[0106] Its derivative formula is: .

[0107] Real-time signals are acquired through sensor units, real-time BP neural network parameters are calculated, and sliding mode control values ​​are obtained through sliding mode control formulas. Based on the negative gradient rule, the connection weights between the output layer and hidden layers are adjusted in real time by combining the sliding mode control values, learning rate, and momentum factor, and a real-time performance index function is obtained.

[0108] First, the setpoint and actual output values ​​of the electro-hydraulic servo system at time z are sampled, and the deviation value, input value of the input layer, input value of the hidden layer, and output value of the output layer are calculated sequentially to obtain the three initial control parameters for sliding mode control. Sliding mode control values ​​are obtained using the sliding mode control formula, and a performance index function is set to measure the control effect. Finally, based on the negative gradient rule, combined with the set learning rate and momentum factor, the connection weights between the output layer and the hidden layer are adjusted, and the performance index function value is updated in real time. Learning ends when the performance index function value is less than the setpoint of the electro-hydraulic servo system; otherwise, iterative sampling and calculation continue until the performance index function value is less than the setpoint of the electro-hydraulic servo system, achieving real-time adaptive optimization of the parameters.

[0109] The formula for the deviation value is: , where r(z) represents the set value of the electro-hydraulic servo system, y(z) represents the actual output value, and e(z) represents the deviation value.

[0110] The input formula in the input layer is: ;

[0111] The hidden layer input formula is: , among which, net i (2) Let w represent the net input value of the i-th hidden layer neuron at the current time, M represent the total number of input layer neurons, and w represent the net input value of the i-th hidden layer neuron. ij (2) This represents the weight connecting the j-th input layer neuron to the i-th hidden layer neuron; o j (1) This represents the output value of the j-th input layer neuron at the current time.

[0112] The hidden layer output formula is: , where o j (1) (z) represents the output value of the j-th input layer neuron at time z; f(neti) (2) (z) is the activation function of the hidden layer.

[0113] The input formula for the output layer is: .

[0114] The output formula of the output layer is: .

[0115] Take o j (1) (z) is the sliding surface coefficient, o j (2) (z) is the reaching law coefficient, o j (3) (z) is the gain coefficient of the switching term. The initial value of the performance index function is selected by the performance index function formula, which is: , where E(z) represents the numerical value of the performance index function.

[0116] Given a learning rate and momentum factor, when the learning rate is η, the output layer connection weights are optimized and adjusted according to the negative gradient rule, using the following formula: ;

[0117] in: ;

[0118] After simplification and approximation, the final change in the connection weights of the output layer after learning is obtained, as shown in the formula:

[0119] ;

[0120] .

[0121] The change in the hidden layer connection weights after learning is expressed by the following formula:

[0122] ;

[0123] .

[0124] The performance index function value is updated in real time. When the performance index function value is less than the set value of the electro-hydraulic servo system, it means that the three parameter values ​​output by the BP neural network have met the requirements of sliding mode control, and the learning calculation ends thereafter. If the performance index function value is greater than or equal to the set value of the electro-hydraulic servo system, z = z + 1 is set, and the learning calculation continues.

[0125] The S-function module of sliding mode control is initialized and set to 7 inputs and 4 outputs. The inputs include relevant signals of the electro-hydraulic servo system status, and the outputs include control variables and three optimized control parameters. At the same time, the S-function has built-in three discrete state variables: deviation, deviation sum, and deviation change, which can provide data storage and interaction support for the execution of control logic.

[0126] To further explain, such as Figure 9 As shown, the electro-hydraulic servo high-frequency output force control model includes:

[0127] Establish a spatial prediction unit for electro-hydraulic servo output force.

[0128] The constraints of the control mechanical load module are obtained through comprehensive calculation using the cost function unit.

[0129] The continuous output force control quantity is obtained by comprehensively applying the quadratic programming formula and constraints.

[0130] In this embodiment, by establishing an electro-hydraulic servo output force spatial prediction unit, the future dynamic response of the electro-hydraulic servo system can be predicted in advance. By combining the cost function minimization objective and constraints, the control problem is transformed into a quadratic programming problem to solve for the optimal control quantity. This can effectively suppress the influence of disturbances, ensure the stability and accuracy of the force output, and meet the high precision requirements of the mechanical load module for output force control.

[0131] The electro-hydraulic servo output force spatial prediction unit includes:

[0132] The basic equations of the valve-controlled symmetrical cylinder are subjected to Laplace transform and simplification to obtain a single-input single-output difference equation.

[0133] By setting the sampling time and constructing the spatial prediction characteristics of the electro-hydraulic servo output force in the prediction time domain through a single-input single-output difference equation, a sampling time is set.

[0134] To further clarify, the basic equations of a valve-controlled symmetrical cylinder include:

[0135] , where Q L K represents the load flow rate of the hydraulic cylinder. q The x represents the flow gain coefficient of the servo valve. v K represents the displacement of the servo valve spool. c p represents the flow-pressure coefficient of the servo valve. L This indicates the load pressure of the hydraulic cylinder;

[0136] Where A represents the effective working area of ​​the hydraulic cylinder piston, y represents the displacement of the hydraulic cylinder piston, and C... ip V represents the internal leakage coefficient of a hydraulic cylinder. t β represents the total volume of the two chambers of a hydraulic cylinder. e This indicates the effective bulk modulus of hydraulic oil. This indicates the speed of the hydraulic cylinder piston. This indicates the rate of change of load pressure;

[0137] Where Fg represents the driving force of the hydraulic cylinder piston, m represents the total mass of the piston and the mechanical load module, Bc represents the damping coefficient of the mechanical load module, K represents the spring stiffness of the elastic element, and F represents the external disturbance force acting on the mechanical load module. This indicates the acceleration of the piston in the hydraulic cylinder.

[0138] Performing a Laplace transform on the above three equations yields:

[0139] ;

[0140] ;

[0141] .

[0142] Assuming the rightward force of the electro-hydraulic servo system is positive, the basic equations of the electro-hydraulic servo system are obtained as follows:

[0143]

[0144]

[0145]

[0146] Simultaneous equations for obtaining the output equations of the electro-hydraulic servo system:

[0147]

[0148] Since the load damping coefficient is small and negligible, the output equation of the electro-hydraulic servo system simplifies to:

[0149] , where K F This represents the damping coefficient of the electro-hydraulic servo system.

[0150] Since the disturbance displacement is not a controllable input, the output equation of the electro-hydraulic servo system is simplified to a single-input single-output mode, and the specific formula is as follows:

[0151]

[0152] Taking a sampling time of 1ms, the output equation of the electro-hydraulic servo system is transformed into a difference equation: ;

[0153] in,

[0154] The state variables are selected as follows:

[0155] in:

[0156] The spatial prediction features of the output equation of the electro-hydraulic servo system are represented as follows:

[0157]

[0158] in,

[0159]

[0160] If the current time is k, then the spatial prediction features in the prediction time domain [k, k+N] are represented as follows:

[0161]

[0162] After processing, the final spatial prediction features are obtained, represented as follows:

[0163] .

[0164] Furthermore, the constraints of the control mechanical load module, obtained through comprehensive calculation using the cost function unit, include:

[0165] The cost function formula is designed with the goal of minimizing the deviation between the system variables and the desired variables, as well as the sum of the input signal amplitudes. A weight matrix is ​​introduced to simplify the function error in the cost function formula.

[0166] The valve core displacement of the solenoid valve assembly and the axial force output by the hydraulic cylinder are set as constraints, and the constraints are obtained through the cost function formula.

[0167] In this embodiment, by constructing a cost function J, the deviation values ​​between each variable of the electro-hydraulic servo system and the expected variable, as well as the minimum cumulative value of the input signal amplitude, are solved in the prediction time domain. This improves the trajectory tracking performance of the electro-hydraulic servo system, ensures the control effect of the spatial prediction features, and allows for real-time optimization and control of the deviation between the state variables and the input quantities of the electro-hydraulic servo system.

[0168] To ensure the effectiveness of model predictive control design and achieve the goal of rapid and stable tracking of the electro-hydraulic servo system, it is necessary to optimize and control the deviation between the system state variables and the input quantities.

[0169] The specific mathematical expression is as follows: Where N represents the prediction time domain length, X k Let X represent the state variable vector of the electro-hydraulic servo system at time k. d Let λ represent the desired state vector of the electro-hydraulic servo system, λ represent the weighting coefficient of the control input, and U(k) represent the control input vector at time k.

[0170] The tracking error E is obtained by subtracting the predicted trajectory from the desired trajectory. The specific formula is as follows: .

[0171] The error function for trajectory tracking is expressed as:

[0172] ;

[0173] in, and Represents the weight matrix;

[0174] make , , , Then the error function for trajectory tracking can be simplified to: , where Z represents the error term determined by the state vector and the desired trajectory, S represents the weighted quadratic form of the error term Z, F represents the weighted coupling term of the error term Z with the input matrix C, and H represents the weighted quadratic coefficient matrix for the control input.

[0175] Set constraints to limit the valve core displacement of the solenoid valve assembly. If necessary, limit the valve core displacement to within ±X mm. In addition, if necessary, limit the axial force output by the hydraulic cylinder to within ±YN.

[0176] Substituting the state and output conditions of the electro-hydraulic servo system into the cost function, the error minimization problem is transformed into a quadratic programming problem, and the control variables in the prediction time domain are obtained. The specific formula is as follows:

[0177] U k Indicates a control scalar.

[0178] like Figures 10-11 As shown, step S3 includes: using a dual-input single-output fuzzy control model based on a correction factor, integrating continuous displacement control and continuous output force control, adjusting displacement control and output force control to a continuous switching state, and continuously controlling the mechanical load module.

[0179] To further clarify, the fuzzy control model includes:

[0180] The sensor unit collects vibration displacement signals and outputs force signals.

[0181] The vibration frequency is calculated, and the displacement signal and output force signal are linearly normalized to obtain the displacement and output force in the range of [0,1].

[0182] The displacement and output force are fuzzified into 5 fuzzy sets by a two-dimensional fuzzy control with dual input and single output, and a fuzzy rule base is established based on the correspondence between displacement and output axial force.

[0183] Using the triangular membership function, the fuzzy inference outputs a control correction factor in the range [0,1].

[0184] By using a fusion formula, displacement and output force are fused and adjusted to obtain displacement and output force in continuously switching states.

[0185] In this embodiment, the dual-input single-output fuzzy control model based on the correction factor can coordinate the control of displacement and output force, achieving smooth switching between output force and displacement of the electro-hydraulic servo system. Therefore, when the horizontal excitation unit and the vertical loading unit cooperate in linear friction welding, the model can control the horizontal excitation unit and the vertical loading unit to work together dynamically. Based on the fuzzy rule base established by the dual-input single-output model, the model can infer the working condition requirements in real time and dynamically adjust the weights of displacement control and output force control. When the vibration frequency of the electro-hydraulic servo system is high, priority is given to ensuring displacement tracking accuracy. When the output force fluctuates greatly, priority is given to stabilizing the force output, achieving continuous and smooth switching between displacement and output force, avoiding control conflicts, improving the coordination and stability of the electro-hydraulic servo system, and further optimizing the weld quality.

[0186] The sensor unit collects the vibration displacement signal of the horizontal excitation unit and the output force feedback signal of the vertical force loading unit in real time, and then calculates the vibration frequency. Specifically, the vibration period is extracted from the displacement signal, the vibration frequency is calculated, and normalization is performed to obtain the frequency normalization value; the output axial force feedback signal is normalized to obtain the output force normalization value.

[0187] Based on the normalized frequency value and the normalized output axial force value, a control correction factor is output through a fuzzy inference algorithm. The value range of the control correction factor is [0,1]. The control correction factor is used to adjust the weights of the displacement control input and the output axial force control input. When α is 1, it is displacement control; when α is 0, it is output force control.

[0188] Based on the correction factor α output by the fuzzy controller, the displacement control input value and the output axial force control input value are weighted and adjusted. The final control input is used by the electro-hydraulic servo system to achieve coordinated control of the horizontal excitation unit and the direct-load unit, specifically:

[0189] First, the input variables are fuzzified, that is, the continuous input signal is converted into a discrete fuzzy set. Specifically, the vibration frequency is processed by linear normalization, and the range becomes [0,1]. The formula is as follows: Where f represents the value of the original input variable, f min and f max These are the minimum and maximum values ​​of the input variable, respectively.

[0190] The input variables are then fuzzified into the following types of fuzzy sets:

[0191] Fuzzy set: {Very low frequency, Low frequency, Mid frequency, High frequency, Very high frequency}

[0192] Fuzzy universe of discourse: {VL, L, M, H, VH}.

[0193] Because triangular membership functions have a simple shape, membership degrees can be easily obtained, and robustness is good, they are chosen for fuzzy membership. The definition of the fuzzy membership function is as follows:

[0194] .

[0195] The output axial force is further normalized, and its range is compressed to [0,1]. The formula is as follows: .

[0196] Based on the range of variation of the output axial force, it is fuzzified into the following fuzzy set:

[0197] Fuzzy set: {very small force, small force, medium force, large force, very large force};

[0198] Fuzzy universe of discourse: {VL, L, M, H, VH}.

[0199] The output axial force is fuzzified using a triangular membership function.

[0200] .

[0201] A fuzzy rule base is established based on the correspondence between displacement and output axial force, which includes the relationship between vibration frequency, output axial force, and correction factor.

[0202] Vibration frequency / axial force VL L M H VH VL H H M M L L H M M L L M M M L L S H M L L S S VH L L S S S

[0203] Based on the input vibration frequency and the fuzzy membership value of the output axial force, the correction factor is calculated using a fuzzy rule base, and the formula is as follows:

[0204] , where μ i z represents the activation strength of the i-th fuzzy control rule. i Let α represent the correction factor corresponding to the i-th fuzzy rule.

[0205] Finally, the obtained correction factors are fused and weighted to adjust the weights of the displacement control input and output forces, and the final control value is output. The fusion formula is as follows:

[0206] , where u disp Indicates the displacement input value, u force α represents the output force input value, α represents the correction factor, and μ represents the output control value.

[0207] It should be understood that the specific embodiments described above are for illustrative purposes only and are not intended to limit the scope of the invention. Obvious variations or modifications derived from the spirit of the invention are still within the protection scope of the invention.

Claims

1. A method for controlling high-frequency displacement and output force in an electro-hydraulic servo system, characterized in that, include: S1: Construct an electro-hydraulic servo high-frequency system The electro-hydraulic servo high-frequency system includes: a hydraulic oil tank, a hydraulic pump connected to the hydraulic oil tank via a hydraulic circuit, an electric motor for driving the hydraulic pump, several hydraulic cylinders connected to the hydraulic oil tank via a hydraulic circuit, a solenoid valve group installed on the main oil inlet for reversing connection, an overflow valve installed on the main oil inlet, a sensor unit for real-time signal acquisition, and a mechanical load module, wherein the several hydraulic cylinders are used to control the operation of the mechanical load module; S2: Based on the electro-hydraulic servo high-frequency system, construct an electro-hydraulic servo high-frequency displacement control model and an electro-hydraulic servo high-frequency output force control model, and obtain the continuous displacement control quantity and the continuous output force control quantity. S3: A dual-input single-output fuzzy control model based on a correction factor integrates continuous displacement control and continuous output force control, adjusts displacement control and output force control to a continuously switching state, and continuously controls the mechanical load module.

2. The high-frequency displacement and output force control method for the electro-hydraulic servo system according to claim 1, characterized in that, The mechanical load module includes a horizontal excitation unit and a vertical loading unit. Both the horizontal excitation unit and the vertical loading unit include a mass block installed at the end of the hydraulic cylinder piston rod, a damper installed on the mass block, and an elastic element sleeved on the outside of the damper. The extension and retraction of the hydraulic cylinder piston rod controls the extension and retraction of the damper.

3. The high-frequency displacement and output force control method for the electro-hydraulic servo system according to claim 1, characterized in that, The electro-hydraulic servo high-frequency displacement control model includes: A three-state control unit is constructed to obtain real-time feedback signals of the three states, and the damping ratio of the mechanical load module is controlled in a comprehensive manner to obtain the deviation signal; Construct a BP neural network sliding mode control unit; The deviation signal is learned in real time through a learning algorithm, and the parameters of the mechanical load module are optimized in real time. The continuous displacement control quantity is obtained through comprehensive calculation.

4. The high-frequency displacement and output force control method for the electro-hydraulic servo system according to claim 3, characterized in that, The construction of the three-state control unit and the acquisition of real-time feedback signals for the three states include: Set up a feedforward stage and a feedback stage, and obtain the feedback coefficients based on the open-loop transfer function formula; The expected closed-loop transfer function of the feedforward stage is obtained by comprehensively using the feedback coefficients. By setting the value of the feedforward transfer function to be equal to the value of the open-loop transfer function, the near-imaginary poles in the closed-loop transfer function are eliminated, thereby expanding the bandwidth and obtaining the real-time feedback signal in three states.

5. The high-frequency displacement and output force control method for the electro-hydraulic servo system according to claim 3, characterized in that, The construction of the BP neural network sliding mode control unit includes: Set up a three-layer output mode consisting of an input layer, a hidden layer, and an output layer; and set the input value, the actual output value, and the deviation value. Initialize the connection weights between the hidden layer and the output layer to random numbers in the range of [-1~1]; The hyperbolic tangent function is used to calculate the input values ​​of the hidden layer, and the non-negative hyperbolic tangent function is used to calculate the input values ​​of the output layer, finally obtaining the output values ​​of the output layer; Real-time BP neural network parameters are calculated by acquiring signals in real time, and sliding mode control values ​​are obtained by combining them through sliding mode control formula. Based on the negative gradient rule, the connection weights between the output layer and the hidden layer are adjusted in real time by combining the sliding mode control value, learning rate and momentum factor, and the real-time performance index function is obtained.

6. The high-frequency displacement and output force control method for an electro-hydraulic servo system according to claim 1, characterized in that, The electro-hydraulic servo high-frequency output force control model includes: Establish a spatial prediction unit for electro-hydraulic servo output force; The constraints for controlling the mechanical load module are obtained through comprehensive calculation using the cost function unit. The continuous output force control quantity is obtained by comprehensively applying the quadratic programming formula and constraints.

7. The high-frequency displacement and output force control method for an electro-hydraulic servo system according to claim 6, characterized in that, The electro-hydraulic servo output force spatial prediction unit includes: The basic equations of the valve-controlled symmetrical cylinder are subjected to Laplace transform and simplification to obtain a single-input single-output difference equation. By setting the sampling time and constructing the spatial prediction characteristics of the electro-hydraulic servo output force in the prediction time domain through a single-input single-output difference equation, a sampling time is set.

8. The high-frequency displacement and output force control method for an electro-hydraulic servo system according to claim 6, characterized in that, The constraint conditions for controlling the mechanical load module are obtained through comprehensive calculation by the cost function unit, including: The cost function formula is designed with the goal of minimizing the deviation between the system variables and the desired variables and the sum of the input signal amplitudes. A weight matrix is ​​introduced to simplify the function error in the cost function formula. The valve core displacement of the solenoid valve assembly and the axial force output by the hydraulic cylinder are set as constraints, and the constraints are obtained through the cost function formula.

9. The high-frequency displacement and output force control method for an electro-hydraulic servo system according to claim 1, characterized in that, Fuzzy control models include: The sensor unit acquires vibration displacement signals and outputs force signals; The vibration frequency is calculated, and the displacement signal and output force signal are linearly normalized to obtain the displacement and output force in the range of [0,1]. The displacement and output force are fuzzified into 5 fuzzy sets by a two-dimensional fuzzy control with dual input and single output, and a fuzzy rule base is established based on the correspondence between displacement and output axial force. Using the triangular membership function, the fuzzy inference outputs a control correction factor in the range [0,1]. By using a fusion formula, displacement and output force are fused and adjusted to obtain displacement and output force in continuously switching states.

10. The high-frequency displacement and output force control method for an electro-hydraulic servo system according to claim 9, characterized in that, The fusion formula is as follows: Where α represents the control correction factor, u disp Indicates the displacement input, u force This indicates the amount of output force input.

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