Electro-hydraulic servo multi-parameter online parallel identification method based on extended observation network

Abstract

The application discloses an electro-hydraulic servo multi-parameter online parallel identification method based on an extended observer network, and the method comprises the following steps: establishing a third-order state space model of an electro-hydraulic servo system according to electro-hydraulic servo system information; obtaining a plurality of synchronous identification parameter extension systems according to the third-order state space model of the electro-hydraulic servo system; obtaining an extended observer network based on the plurality of synchronous identification parameter extension systems, and performing online parallel identification on the multi-parameters of the electro-hydraulic servo system through the extended observer network. Compared with the online identification method in the prior art, the friction and external disturbance are not considered, which makes the estimation accuracy not high, and the application of the extended state observer to the electro-hydraulic servo system parameter identification field ensures the strong robustness of the system parameter identification process to the external dynamic disturbance and noise, greatly saves the time cost of multi-parameter identification, and provides strong support for the accurate control algorithm and dynamic disturbance compensation of the electro-hydraulic servo.

Description

Technical Field

[0001] This invention relates to the field of parameter identification technology for electro-hydraulic servo systems, and in particular to an online parallel identification method for multiple parameters of electro-hydraulic servo systems based on an extended observation network. Background Technology

[0002] Electro-hydraulic servo valve-controlled asymmetric cylinder systems are widely used in various large-scale mechanical and electronic engineering projects due to their advantages such as small size, simple structure, and high load capacity. Their position, speed, and pressure response performance and control accuracy are important indicators for evaluating their control systems.

[0003] Currently, system parameter identification techniques are mainly divided into two categories: offline identification and online identification. Offline identification techniques can only be used during control system commissioning, and these methods have poor robustness. Compared to offline identification, online identification techniques are applicable to more complex situations. Model reference adaptation, recursive least squares, and gradient algorithms are commonly used online algorithms for identifying mass and viscous damping coefficients, and they are popular due to their low computational burden. However, these online identification methods do not consider friction and external disturbances, which makes their estimation accuracy low. Methods based on optimal parameter estimation have some robustness to external disturbances, but due to their large number of matrix operations, they are difficult to implement in industrial applications. Therefore, ensuring strong robustness of the system parameter identification process against external dynamic disturbances and noise has become an urgent problem to be solved.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this invention is to provide an online parallel identification method for multiple parameters of electro-hydraulic servo based on an extended observation network, aiming to address the technical problem of how to ensure the robustness of the system parameter identification process against external dynamic disturbances and noise.

[0006] To achieve the above objectives, this invention provides an online parallel identification method for multiple parameters of electro-hydraulic servo based on an extended observation network. The online parallel identification method for multiple parameters of electro-hydraulic servo based on an extended observation network includes:

[0007] A third-order state-space model of the electro-hydraulic servo system is established based on the information of the electro-hydraulic servo system.

[0008] Based on the third-order state-space model of the electro-hydraulic servo system, multiple synchronous identification parameter extension systems are obtained;

[0009] An extended observer network is obtained by extending the system based on multiple synchronous identification parameters, and multiple parameters of the electro-hydraulic servo system are identified online in parallel through the extended observer network.

[0010] Optionally, the cylinder driving force is determined by determining the pressure in the rodless chamber of the hydraulic cylinder, the pressure in the rod chamber of the hydraulic cylinder, the working area of ​​the rodless chamber of the hydraulic cylinder, and the working area of ​​the rod chamber of the hydraulic cylinder based on the information from the electro-hydraulic servo system.

[0011] The corresponding rodless chamber working flow rate and rod chamber working flow rate are determined based on the pressure of the rodless chamber of the hydraulic cylinder, the pressure of the rod chamber of the hydraulic cylinder, the oil supply pressure of the electro-hydraulic servo system, the oil return pressure of the electro-hydraulic servo system, the total gain coefficient of the electro-hydraulic servo valve, the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber of the cylinder, and the working volume of the rod chamber of the cylinder, respectively.

[0012] A third-order state-space model of the electro-hydraulic servo system is constructed based on the cylinder driving force, the working flow rate of the rodless cavity, the working flow rate of the rod cavity, and the state variables of the electro-hydraulic servo system.

[0013] Optionally, the step of determining the cylinder driving force by determining the pressure in the rodless chamber, the pressure in the rod chamber, the working area of ​​the rodless chamber, and the working area of ​​the rod chamber based on the electro-hydraulic servo system information includes:

[0014] Based on the information from the electro-hydraulic servo system, the pressure in the rodless chamber, the pressure in the rod chamber, the working area of ​​the rodless chamber, and the working area of ​​the rod chamber are determined. The driving force of the cylinder is then obtained through the force balance formula of the load of the valve-controlled asymmetric hydraulic cylinder system.

[0015] The force balance formula for the load of the valve-controlled asymmetric hydraulic cylinder system is:

[0016]

[0017] F e =p1A1-p2A2

[0018] In the formula, m is the equivalent total mass of the piston rod and the load. Let be the second derivative of the displacement, p1 be the pressure in the rodless chamber of the hydraulic cylinder, p2 be the pressure in the rod chamber of the hydraulic cylinder, A1 be the working area of ​​the rodless chamber of the hydraulic cylinder, A2 be the working area of ​​the rod chamber of the hydraulic cylinder, K be the load spring stiffness, y be the piston rod displacement, and B be the load damping coefficient. F is the first derivative of the displacement. L For the equivalent external load force and its unknown dynamic disturbance, F e This is the driving force for the hydraulic cylinder.

[0019] Optionally, the step of determining the working flow rate of the rodless chamber and the working flow rate of the rod chamber based on the pressure of the rodless chamber of the hydraulic cylinder, the pressure of the rod chamber of the hydraulic cylinder, the oil supply pressure of the electro-hydraulic servo system, the oil return pressure of the electro-hydraulic servo system, the total gain coefficient of the electro-hydraulic servo valve, the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber of the cylinder, and the working volume of the rod chamber of the cylinder includes:

[0020] The working flow rates of the rodless chamber and the rod chamber are obtained by using the servo valve flow continuity formula based on the pressure of the rodless chamber of the hydraulic cylinder, the pressure of the rod chamber of the hydraulic cylinder, the oil supply pressure of the electro-hydraulic servo system, and the total gain coefficient of the electro-hydraulic servo valve.

[0021] The formula for the continuity of the servo valve flow rate is:

[0022]

[0023]

[0024] In the formula, sign(·) is the sign function, Q1 is the working flow rate of the rodless cavity, Q2 is the working flow rate of the rod cavity, and p s The oil supply pressure for the electro-hydraulic servo system is given by u, where u is the control input signal for the servo valve, and k is the oil supply pressure. t This refers to the overall gain coefficient of the servo valve.

[0025] Based on the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber of the cylinder, and the working volume of the rod chamber of the cylinder, the working flow rate of the rodless chamber and the working flow rate of the rod chamber are obtained through the flow continuity formula of the asymmetric hydraulic cylinder.

[0026] The flow continuity formula for the asymmetric hydraulic cylinder is:

[0027]

[0028] In the formula, C ip C is the internal leakage coefficient of the hydraulic cylinder. ep β is the external leakage coefficient of the hydraulic cylinder. e V1 is the elastic modulus of the hydraulic oil, V2 is the working volume of the rodless chamber of the hydraulic cylinder, and V3 is the working volume of the rod-side chamber of the hydraulic cylinder. and These are the time derivatives of V1 and V2, respectively; and These are the time derivatives of p1 and p2, respectively.

[0029] Optionally, the step of constructing a third-order state-space model of the electro-hydraulic servo system based on the cylinder driving force, the working flow rate of the rodless chamber, the working flow rate of the rod chamber, and the state variables of the electro-hydraulic servo system includes:

[0030] Based on the hydraulic cylinder driving force, the working flow rate of the rodless chamber, the working flow rate of the rod chamber, and the state variables of the electro-hydraulic servo system, a third-order state space model of the electro-hydraulic servo system is constructed using a preset vector formula.

[0031] The preset vector formula is:

[0032]

[0033]

[0034]

[0035] In the formula, C ip C is the internal leakage coefficient of the hydraulic cylinder. ep β is the external leakage coefficient of the hydraulic cylinder. e Let y0 be the elastic modulus of the hydraulic oil, L be the effective stroke of the piston rod, and y0 be the initial position of the piston rod. Let x1 be the derivative of the hydraulic cylinder driving force, and x2, x3 be the state vectors. and Let x1, x2, and x3 be the time derivatives of the state vectors x1, x2, and x3.

[0036] Optionally, the step of obtaining multiple synchronization identification parameters of the extended system based on the third-order state-space model of the electro-hydraulic servo system includes:

[0037] Based on the third-order state-space model of the electro-hydraulic servo system, multiple synchronous identification parameter extension systems are obtained through the hydraulic system motion balance formulas corresponding to multiple synchronous identification parameters. The multiple synchronous identification parameters include the equivalent total mass of the piston rod and the load, the load damping coefficient, the equivalent external load force and its unknown dynamic disturbance. The multiple synchronous identification parameter extension systems include the equivalent total mass extension system of the piston rod and the load, the load damping coefficient extension system, and the equivalent external load force and its unknown dynamic disturbance extension system.

[0038] The hydraulic system motion balance formulas corresponding to multiple synchronous identification parameters are as follows:

[0039] Σ1:

[0040] Σ2:

[0041] Σ3:

[0042] In the formula, v i (i = 1, 2, 3) represents the velocity. For acceleration, F ei (i = 1, 2, 3) represents the driving force of the hydraulic cylinder, and a1, a2, and a3 represent r, B, and F, respectively. LThe time derivative of Σ1 is the reciprocal of the load mass, Σ2 is the extended system of the equivalent total mass of the piston rod and the load, and Σ3 is the extended system of the load damping coefficient and its unknown dynamic disturbance.

[0043] Optionally, the step of obtaining the extended observer network based on the extended system using multiple synchronous identification parameters includes:

[0044] The system based on multiple synchronous identification parameters obtains multiple extended observers through the extended state observer formula;

[0045] The formula for the extended state observer is:

[0046] O1:

[0047] O2:

[0048] O3:

[0049] In the formula, O i (i = 1, 2, 3) represents multiple extended observers. For the observed values, for Time derivative, for Time derivative, for Time derivative, for Time derivative, e ESO1_1 e ESO2_1 e ESO3_1 For observation error, For the maximum acceleration threshold, |v max | represents the maximum speed threshold;

[0050] An extended observer network is generated based on multiple extended observers.

[0051] Furthermore, to achieve the above objectives, this invention also proposes an online parallel identification system for multiple parameters of an electro-hydraulic servo based on an extended observation network. The online parallel identification system for multiple parameters of an electro-hydraulic servo based on an extended observation network includes:

[0052] A module is established to build a third-order state-space model of the electro-hydraulic servo system based on the information of the electro-hydraulic servo system.

[0053] The determination module is used to obtain multiple synchronization identification parameters for the extended system based on the third-order state-space model of the electro-hydraulic servo system;

[0054] The processing module is used to expand the system based on multiple synchronous identification parameters to obtain an expanded observer network, and to perform online parallel identification of multiple parameters of the electro-hydraulic servo system through the expanded observer network.

[0055] Furthermore, to achieve the above objectives, the present invention also proposes an online parallel identification device for electro-hydraulic servo multi-parameters based on an extended observation network. The device includes: a memory, a processor, and an online parallel identification program for electro-hydraulic servo multi-parameters based on an extended observation network stored in the memory and executable on the processor. The online parallel identification program for electro-hydraulic servo multi-parameters based on an extended observation network is configured to implement the steps of the online parallel identification method for electro-hydraulic servo multi-parameters based on an extended observation network as described above.

[0056] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing an online parallel identification program for multiple parameters of an electro-hydraulic servo based on an extended observation network. When the online parallel identification program for multiple parameters of an electro-hydraulic servo based on an extended observation network is executed by a processor, it implements the steps of the online parallel identification method for multiple parameters of an electro-hydraulic servo based on an extended observation network as described above.

[0057] This invention first establishes a third-order state-space model of the electro-hydraulic servo system based on its information. Then, it obtains multiple synchronous identification parameter extension systems based on this model. Subsequently, it generates an extended observer network based on these extended systems and performs online parallel identification of multiple parameters of the electro-hydraulic servo system through this network. Compared to existing online identification methods that do not consider friction and external disturbances, resulting in low estimation accuracy, this invention applies an extended state observer to the field of electro-hydraulic servo system parameter identification. This ensures strong robustness of the system parameter identification process against external dynamic disturbances and noise, significantly reducing the time cost of multi-parameter identification and providing powerful support for precise control algorithms and dynamic disturbance compensation in electro-hydraulic servo systems. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of the structure of an electro-hydraulic servo multi-parameter online parallel identification device based on an extended observation network, which is part of the hardware operating environment of the embodiment of the present invention.

[0059] Figure 2 This is a flowchart illustrating the first embodiment of the online parallel identification method for multiple parameters of electro-hydraulic servo based on an extended observation network according to the present invention.

[0060] Figure 3 This is a schematic diagram of a valve-controlled asymmetric cylinder system, representing the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network according to the present invention.

[0061] Figure 4 This is an extended observer network diagram of the first embodiment of the online parallel identification method for electro-hydraulic servo multi-parameter based on an extended observer network according to the present invention.

[0062] Figure 5 This is a block diagram of the principle of the extended observer for the identification quality m in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network of the present invention.

[0063] Figure 6 This is a block diagram of the principle of the extended observer for identifying the viscous damping coefficient B in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network of the present invention.

[0064] Figure 7 This is the first embodiment of the online parallel identification method for multi-parameter electro-hydraulic servo based on extended observation network of the present invention for identifying external load force F. L Block diagram of the extended observer principle;

[0065] Figure 8 The figure shows the simulation observation results of the online parallel identification method for mass m in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on the extended observation network of the present invention.

[0066] Figure 9 The figure shows the simulation observation results of the viscous friction coefficient B of the first embodiment of the online parallel identification method for electro-hydraulic servo multi-parameter identification based on extended observation network of the present invention.

[0067] Figure 10 This invention provides a first embodiment of an online parallel identification method for electro-hydraulic servo multi-parameter identification based on an extended observation network. The method addresses external loads and disturbances F. L The simulation observation results are shown in the figure.

[0068] Figure 11 This is a structural block diagram of the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification system based on an extended observation network according to the present invention.

[0069] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0070] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0071] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of an electro-hydraulic servo multi-parameter online parallel identification device based on an extended observation network, which is part of the hardware operating environment of the embodiment of the present invention.

[0072] like Figure 1 As shown, the electro-hydraulic servo multi-parameter online parallel identification device based on an extended observation network may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. The memory 1005 may also optionally be a storage system independent of the aforementioned processor 1001.

[0073] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the electro-hydraulic servo multi-parameter online parallel identification device based on the extended observation network. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0074] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and an online parallel identification program for electro-hydraulic servo multi-parameters based on an extended observation network.

[0075] exist Figure 1 In the online parallel identification device for electro-hydraulic servo multi-parameters based on an extended observation network shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and memory 1005 in the online parallel identification device for electro-hydraulic servo multi-parameters based on an extended observation network can be set in the device. The online parallel identification device for electro-hydraulic servo multi-parameters based on an extended observation network calls the online parallel identification program for electro-hydraulic servo multi-parameters based on an extended observation network stored in the memory 1005 through the processor 1001, and executes the online parallel identification method for electro-hydraulic servo multi-parameters based on an extended observation network provided in the embodiment of the present invention.

[0076] This invention provides an online parallel identification method for multiple parameters of electro-hydraulic servo based on an extended observation network, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network according to the present invention.

[0077] In this embodiment, the online parallel identification method for multiple parameters of electro-hydraulic servo based on extended observation network includes the following steps:

[0078] Step S10: Establish a third-order state-space model of the electro-hydraulic servo system based on the electro-hydraulic servo system information.

[0079] It is easy to understand that the execution subject of this embodiment can be an electro-hydraulic servo multi-parameter online parallel identification device based on an extended observation network, which has functions such as data processing, network communication and program execution, or other computer devices with similar functions. This embodiment does not limit it.

[0080] In this embodiment, the process of establishing a third-order state-space model of the electro-hydraulic servo system based on the electro-hydraulic servo system information is as follows: The hydraulic cylinder driving force is determined by calculating the pressure in the rodless chamber, the pressure in the rod chamber, the working area of ​​the rodless chamber, and the working area of ​​the rod chamber. Then, the corresponding rodless chamber working flow rate and rod chamber working flow rate are determined based on the pressure in the rodless chamber, the pressure in the rod chamber, the oil supply pressure, the oil return pressure, the total gain coefficient of the electro-hydraulic servo valve, the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber, and the working volume of the rod chamber. Finally, a third-order state-space model of the electro-hydraulic servo system is constructed based on the cylinder driving force, the working flow rate of the rodless chamber, the working flow rate of the rod chamber, and the state variables of the electro-hydraulic servo system.

[0081] Furthermore, the method for determining the cylinder driving force based on the information from the electro-hydraulic servo system to determine the pressure in the rodless chamber, the pressure in the rod chamber, the working area in the rodless chamber, and the working area in the rod chamber is as follows: the cylinder driving force is obtained by applying the force balance formula of the load of the valve-controlled asymmetric hydraulic cylinder system based on the information from the electro-hydraulic servo system to the pressure in the rodless chamber, the pressure in the rod chamber, the working area in the rodless chamber, and the working area in the rod chamber.

[0082] Furthermore, the corresponding rodless chamber pressure and rod chamber pressure are determined based on the hydraulic cylinder's rodless chamber pressure, the electro-hydraulic servo system's oil supply pressure, the electro-hydraulic servo system's return pressure, the electro-hydraulic servo valve's total gain coefficient, the cylinder's internal and external leakage coefficients, the cylinder's external leakage coefficient, the hydraulic oil's elastic modulus, and the cylinder's rodless chamber working volume and rod chamber working volume, respectively. A third-order state-space model of the electro-hydraulic servo system is then constructed using a preset vector formula based on the cylinder's driving force, the rodless chamber working flow rate, the rod chamber working flow rate, and the electro-hydraulic servo system's state variables.

[0083] In the specific implementation, refer to Figure 3 , Figure 3 This is a schematic diagram of a valve-controlled asymmetric cylinder system, representing the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network according to the present invention. The main components of the entire system are an electro-hydraulic servo valve and an asymmetric hydraulic cylinder. By inputting an electrical signal to the servo valve to drive the valve core, the flow rate and pressure of the hydraulic fluid are changed to control the asymmetric cylinder to work along the desired trajectory. Figure 3 In the diagram, m represents the equivalent total mass of the piston rod and the load; y represents the piston rod displacement, defined as positive to the right; B is the load damping coefficient; K is the load spring stiffness; F L p1 and p2 are the equivalent external load force and its unknown dynamic disturbance; p1 and p2 are the pressures in the rodless and rod-side chambers of the hydraulic cylinder, respectively; A1 and A2 are the working areas of the rodless and rod-side chambers of the hydraulic cylinder, respectively; Q1 and Q2 are the working flow rates of the rodless and rod-side chambers of the hydraulic cylinder, respectively; p s p represents the system oil supply pressure. r This indicates the return oil pressure, which can be set to 0; u is the valve core electrical signal input.

[0084] Combination Figure 3 The force balance formula for the load of a valve-controlled asymmetric hydraulic cylinder system can be expressed as:

[0085]

[0086] in The second derivative of the displacement is the acceleration. Let F be the first derivative of the displacement, i.e., the velocity. e Then we have:

[0087] F e =p1A1-p2A2 (2)

[0088] Assume the electro-hydraulic servo valve is an ideal zero-opening four-sided spool valve with symmetrical orifices and equal flow coefficients at each orifice. The hydraulic fluid is an ideal liquid, and internal leakage and pressure loss are negligible. Let the servo valve spool displacement be x. v If we define positive as moving right from zero, then the flow rates Q1 and Q2 flowing into and out of the valve can be expressed as follows:

[0089]

[0090] Where sign(·) is the sign function; C d The flow coefficient of the spool valve; w is the area gradient of the spool valve; ρ is the oil density. From equation (3), it can be seen that the flow rate change of the valve is related to the spool displacement x of the servo valve. v Regarding this, considering that most servo valves currently in use are high-frequency servo valves, whose response frequency is much higher than the motion frequency of hydraulic cylinders, the valve spool displacement of a servo valve and the control input of the servo valve can be linearly expressed as:

[0091] x v =k xv u (4)

[0092] In the formula, u is the control input signal of the servo valve, and k xv This is the gain of the servo valve.

[0093] Substituting equation (4) into equation (3), we obtain the formula for the continuity of servo valve flow:

[0094]

[0095]

[0096] In the formula, Q1 is the working flow rate of the rodless cavity, Q2 is the working flow rate of the rod cavity, and p s The oil supply pressure for the electro-hydraulic servo system is given by u, where u is the control input signal for the servo valve, and k is the oil supply pressure. t This represents the total gain coefficient of the servo valve.

[0097] Considering the internal and external leakage of the asymmetric hydraulic cylinder and the compressibility of the hydraulic oil, the flow continuity equation for the asymmetric hydraulic cylinder can be obtained as follows:

[0098]

[0099] Where C ip and C ep These are the internal and external leakage coefficients of the hydraulic cylinder, respectively; β e V1 represents the elastic modulus of the hydraulic oil; V2 and V1 represent the working volumes of the rodless and rod-side chambers of the cylinder, respectively. and These are the time derivatives of V1 and V2, respectively; and Let V1 and V2 be the time derivatives of p1 and p2, respectively. In the formula, V1 and V2 vary with the displacement y of the piston rod. This can be expressed as:

[0100]

[0101] Where L is the effective stroke of the piston rod; y0 is the initial position of the piston rod. According to equation (7), we can obtain... and

[0102]

[0103] Substituting equations (7) and (8) into equation (6), we get:

[0104]

[0105] To construct a reasonable state-space model, the driving force F of the hydraulic cylinder is further analyzed. e Taking the derivative, we can obtain F e derivative for:

[0106]

[0107] Select piston rod displacement y and velocity and the hydraulic cylinder driving force F e As the state variables of the system, the state vector can be represented as:

[0108]

[0109] Combining equations (1), (2), (5), and (10), a third-order state-space model of the valve-controlled asymmetric cylinder system can be obtained. The time derivatives of state vectors x1, x2, and x3 are respectively:

[0110]

[0111]

[0112] The system can be further represented as:

[0113]

[0114]

[0115] For a practical hydraulic cylinder positioning system, there is generally no spring, i.e., K = 0. Combining equations (1) and (2), the system's mechanical equilibrium equations can be simplified to:

[0116]

[0117] in For the piston rod speed, This is the acceleration of the piston rod.

[0118] Step S20: Obtain multiple synchronization identification parameter extension systems based on the third-order state-space model of the electro-hydraulic servo system.

[0119] Furthermore, based on the third-order state-space model of the electro-hydraulic servo system, multiple synchronous identification parameter extension systems are obtained through the hydraulic system motion balance formulas corresponding to multiple synchronous identification parameters. The multiple synchronous identification parameters include the equivalent total mass of the piston rod and the load, the load damping coefficient, and the equivalent external load force and its unknown dynamic disturbance. The multiple synchronous identification parameter extension systems include the equivalent total mass extension system of the piston rod and the load, the load damping coefficient extension system, and the equivalent external load force and its unknown dynamic disturbance extension system.

[0120] In practical implementation, due to the external load force F of the electro-hydraulic servo system L The presence of unknown dynamic disturbances, coupled with the system's inherent unknown viscous damping B and load mass m variations, can lead to a decrease in the dynamic and steady-state performance of its control. This effect is particularly pronounced in systems with asymmetrical cylinders and varying effective areas. Currently, some high-precision algorithms for improving dynamic and steady-state performance rely heavily on accurate identification of system parameters and external load disturbances. Therefore, accurately identifying these system parameters and external loads and their disturbances is crucial. In this embodiment, parameters m, B, and F are identified simultaneously. L By defining the reciprocal r of the load mass, several different extended equations can be constructed as follows:

[0121]

[0122] Σ1:

[0123] Σ2:

[0124] Σ3:

[0125] In the formula, v i (i = 1, 2, 3) represents the velocity. For acceleration, F ei (i = 1, 2, 3) represents the driving force of the hydraulic cylinder, and a1, a2, and a3 represent r, B, and F, respectively. L The time derivative of Σ1 is the reciprocal of the load mass, Σ2 is the extended system of the equivalent total mass of the piston rod and the load, and Σ3 is the extended system of the load damping coefficient and its unknown dynamic disturbance.

[0126] Step S30: Based on multiple synchronous identification parameters, the system is extended to obtain an extended observer network, and the extended observer network is used to perform online parallel identification of multiple parameters of the electro-hydraulic servo system.

[0127] Furthermore, the processing method for obtaining the extended observer network based on the extended system with multiple synchronous identification parameters is to obtain multiple extended observers through the extended state observer formula based on the extended system with multiple synchronous identification parameters, and then generate the extended observer network based on the multiple extended observers.

[0128] In the specific implementation, refer to Figure 4 , Figure 4 This is an extended observer network diagram of the first embodiment of the online parallel identification method for multi-parameter electro-hydraulic servo based on an extended observer network according to the present invention. Based on the extended state observer (ESO) method, three new ESOs were developed to observe the states of systems Σ1, Σ2, and Σ3. In system Σ1, v1 and r are the observation objects, and their observed values ​​are respectively set as... and Take the observation error of v1 Observation error of r An ESO system O1 can be designed for system Σ1:

[0129] O1:

[0130] in They are B and F respectively. L Observed values; and for and Time derivative; β 11 β 12 This is the gain parameter for the extended observer O1.

[0131] Similarly, for systems Σ2 and Σ3, let v2 and B, v3 and F respectively. L As the object of observation, with and and The observed value has an observation error of v2. B's observation error observation error of v3 F L observation error Then there are ESO systems O2 and O3:

[0132] O2:

[0133] O3:

[0134] in and for and The time derivative; and for and Time derivative; β 21 β 22 β is the gain parameter for the extended observer O2. 31 β 32 Let v be the gain parameter of the extended observer O3; where v in the above equation i (i = 1, 2, 3) and F ei (i = 1, 2, 3) can be calculated using displacement sensors and pressure sensors respectively.

[0135] Subtracting equation (17) from equation (20) and performing certain transformations, we obtain the error equations for system Σ1 and observer O1:

[0136]

[0137] in, For e ESO1_1 e ESO1_2 The time derivative.

[0138]

[0139] Similarly, combining equations (18) and (21), and equations (19) and (22), we can derive the error equations for system Σ2 and observer O2, and the error equations for system Σ3 and observer O3:

[0140]

[0141] in, For e ESO2_1 e ESO2_2 The time derivative.

[0142]

[0143]

[0144] in, For e ESO3_1 e ESO3_2 The time derivative.

[0145]

[0146] For system O1, to ensure that the observed velocity of the system converges to the actual velocity of the system in steady state, for β... 11 Make adjustments to make According to equations (23) and (24), F1 * With observation speed It is irrelevant, therefore it is not e. ESO1_1 The function. Substituting it into equation (23) gives:

[0147]

[0148] The convergence of this function is verified below, using the Lyapunov function:

[0149]

[0150] For V1(e) ESO1_1 Differentiating, we have:

[0151]

[0152] Let it be Bounded, and When β 11 >RB * hour, This holds true consistently. That is, the observation rate of system O1 converges.

[0153] Similarly:

[0154] F2 * =R ESO2 e ESO1_2 +B ESO2 e ESO2_2 +F ESO2 e ESO3_2

[0155] F3 * =R ESO3 e ESO1_2 +B ESO3 e ESO2_2 +F ESO3 e ESO3_2

[0156]

[0157]

[0158] Based on the above derivation, it is easy to obtain β. 21 >RB * ,β 31 >RB * hour, The observation rates of systems O2 and O3 converged.

[0159] Here let β 11 =β 21 =β 31 =β, we only need to adjust β so that β > RB * System O i The observation rate converged for (i = 1, 2, 3).

[0160] For observer O1, when the observed velocity and the actual velocity reach a steady state, we have eESO1_1 =0, Substituting into equation (23), we get:

[0161]

[0162] Similarly, for observers O2 and O3, we have:

[0163]

[0164]

[0165] Let β 12 =b1β 11 Substituting equation (24) into equation (32), we get:

[0166]

[0167] Similarly, let β 22 =b2β 21 β 32 =b3β 31 It is easy to obtain:

[0168]

[0169]

[0170] In general, the parameters m, B, and F L The frequency of change of the three parameters is much smaller than the periodic frequency of the control system. Therefore, the three parameters can be considered constant over a very short time. This means that their rate of change a1 = a2 = a3 = 0, and thus:

[0171]

[0172] For (F) e2 -Bv2-F L The term, according to the formula, is equal to the following in the system: For actual servo systems, there exists a maximum acceleration threshold for the driving capability. With the maximum speed threshold |v max |

[0173] To ensure observer convergence, take Substitution formula (38) yields:

[0174]

[0175] Since the reciprocal of the actual mass of the system, r, is bounded, and Therefore when If the integer is close enough to 0, then:

[0176]

[0177] Similarly, and and If the integer is close enough to 0, then:

[0178]

[0179]

[0180] Based on equations (40), (41), and (42), the analytical expression can be derived as follows:

[0181]

[0182] Where C1, C2, and C3 are constants, and the above equation always holds:

[0183] when

[0184] when

[0185] when

[0186] Based on the analytical expression, we can conclude that the estimation error e ESO1_2 e ESO2_2 and e ESO3_2 It converges exponentially to zero with time t. Its convergence rate increases with g. i It increases as (i = 1, 2, 3) increases, and according to the above...

[0187] and and To approach 0, we can conclude that a smaller g... i (i = 1, 2, 3) implies a slower convergence rate and higher estimation accuracy.

[0188] g i (i = 1, 2, 3), b i (i = 1, 2, 3), β 11 =β 21 =β 31 =β etc. Substitute into system O i (i = 1, 2, 3) yields the basic form of the observer:

[0189] O1:

[0190] O2:

[0191]

[0192] The extended observer O is obtained according to equations (44), (45), and (46). i The system block diagram for (i = 1, 2, 3) is shown in Figure 5. Figure 6 and Figure 7 As shown. Figure 5 This is a block diagram of the principle of the extended observer for the identification quality m in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network of the present invention. Figure 6 This is a block diagram of the principle of the extended observer for identifying the viscous damping coefficient B in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network of the present invention. Figure 7 This is the first embodiment of the online parallel identification method for multi-parameter electro-hydraulic servo based on extended observation network of the present invention for identifying external load force F. L The block diagram of the extended observer principle.

[0193] To verify the feasibility and effectiveness of the multi-parameter online parallel identification technology provided in this invention, a corresponding simulation model was built for research. A system and extended observer network model were established in Simulink, with the following simulation parameters set: the velocity command is a square wave with positive and negative changes in direction, with an amplitude of ±0.5 m / s and a change-of-direction time of 1 s; the actual mass m = 20 kg, the actual viscous damping coefficient B = 2000, and the actual external load is a square wave following the velocity's positive and negative changes in direction, with an amplitude of ±1000 N. To verify the system's robustness, noise interference with an amplitude of approximately 5% was added to both the external load and the velocity. The maximum acceleration threshold was also set. Maximum speed threshold | v max |=1. By adjusting the parameters β and g i (i = 1, 2, 3) satisfy the convergence condition, and the parameters m, B, and F can be identified online in parallel. L In fact, according to equation (43), e ESO2_2 The convergence rate with time t is e ESO3_2 v2 2 It is entirely possible to let g3 = g2v2. 2 We only need to adjust the three parameters β, g1, and g2 to satisfy the convergence condition. Here, we take β = 2 × 10 8 g1 = 0.0005, g2 = 1 × 10 7 m, B, and F L Parallel parameter identification results are as follows Figure 8 , Figure 9 and Figure 10 As shown.

[0194] Figure 8This is a simulation observation result of the online parallel identification method for mass m in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on an extended observation network of the present invention; the reciprocal of the mass r = 0.05, the mass converges at 0.25s, and its overall convergence error is ±0.01% of the actual value; Figure 9 The above is a simulation observation result of the online parallel identification method for the viscous friction coefficient B in the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification method based on the extended observation network of the present invention. It completes convergence at 0.2s, and its overall convergence error is ±0.005% of the actual value. When the velocity changes direction and the external load changes abruptly, the error is 0.035% of the actual value. Figure 10 This invention provides a first embodiment of an online parallel identification method for electro-hydraulic servo multi-parameter identification based on an extended observation network. The method addresses external loads and disturbances F. L The simulation observation results show that it converges within 0.0015s after the load jump, and it has good robustness to added noise interference.

[0195] In this embodiment, a third-order state-space model of the electro-hydraulic servo system is first established based on the system information. Then, multiple synchronous identification parameter extension systems are obtained from this model. Subsequently, an extended observer network is derived based on these extended systems, and online parallel identification of multiple parameters of the electro-hydraulic servo system is performed using this network. Compared to existing online identification methods that do not consider friction and external disturbances, resulting in low estimation accuracy, this embodiment applies an extended state observer to the field of electro-hydraulic servo system parameter identification. This ensures strong robustness of the system parameter identification process against external dynamic disturbances and noise, significantly reducing the time cost of multi-parameter identification and providing strong support for precise control algorithms and dynamic disturbance compensation in electro-hydraulic servo systems.

[0196] Reference Figure 11 , Figure 11 This is a structural block diagram of the first embodiment of the electro-hydraulic servo multi-parameter online parallel identification system based on an extended observation network according to the present invention.

[0197] like Figure 11 As shown, the online parallel identification system for electro-hydraulic servo multi-parameters based on an extended observation network proposed in this embodiment of the invention includes:

[0198] Establish module 01, which is used to establish a third-order state-space model of the electro-hydraulic servo system based on the information of the electro-hydraulic servo system;

[0199] The determination module 02 is used to obtain multiple synchronization identification parameter extension systems based on the third-order state-space model of the electro-hydraulic servo system;

[0200] Processing module 03 is used to expand the system based on multiple synchronous identification parameters to obtain an expanded observer network, and to perform online parallel identification of multiple parameters of the electro-hydraulic servo system through the expanded observer network.

[0201] Other embodiments or specific implementations of the electro-hydraulic servo multi-parameter online parallel identification system based on the extended observation network of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0202] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

Claims

1. A method for online parallel identification of multiple parameters of electro-hydraulic servo based on an extended observation network, characterized in that, The online parallel identification method for multiple parameters of electro-hydraulic servo based on extended observation network includes the following steps: A third-order state-space model of the electro-hydraulic servo system is established based on the information of the electro-hydraulic servo system. Based on the third-order state-space model of the electro-hydraulic servo system, multiple synchronous identification parameter extension systems are obtained; An extended observer network is obtained by extending the system based on multiple synchronous identification parameters, and multiple parameters of the electro-hydraulic servo system are identified online in parallel through the extended observer network. The steps for obtaining the extended observer network based on the extended system using multiple synchronous identification parameters include: The system based on multiple synchronous identification parameters obtains multiple extended observers through the extended state observer formula; The formula for the extended state observer is: In the formula, For multiple extended observers, , For the observed values, for Time derivative, for Time derivative, for Time derivative, for Time derivative, For speed, For acceleration, for Time derivative, , , For observation error, The maximum acceleration threshold, The maximum speed threshold, This is the gain parameter; An extended observer network is generated based on multiple extended observers.

2. The method as described in claim 1, characterized in that, The step of establishing a third-order state-space model of the electro-hydraulic servo system based on the information of the electro-hydraulic servo system includes: The hydraulic cylinder driving force is determined by the information from the electro-hydraulic servo system, which includes the pressure in the rodless chamber, the pressure in the rod chamber, the working area of ​​the rodless chamber, and the working area of ​​the rod chamber. The working flow rates of the rodless chamber and the rod chamber are determined based on the pressure of the rodless chamber of the hydraulic cylinder, the pressure of the rod chamber of the hydraulic cylinder, the oil supply pressure of the electro-hydraulic servo system, the oil return pressure of the electro-hydraulic servo system, the total gain coefficient of the electro-hydraulic servo valve, the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber of the cylinder, and the working volume of the rod chamber of the cylinder, respectively. A third-order state-space model of the electro-hydraulic servo system is constructed based on the cylinder driving force, the working flow rate of the rodless cavity, the working flow rate of the rod cavity, and the state variables of the electro-hydraulic servo system.

3. The method as described in claim 2, characterized in that, The step of determining the cylinder driving force by analyzing the pressure in the rodless chamber, the pressure in the rod chamber, the working area of ​​the rodless chamber, and the working area of ​​the rod chamber based on information from the electro-hydraulic servo system includes: Based on the information from the electro-hydraulic servo system, the pressure in the rodless chamber, the pressure in the rod chamber, the working area of ​​the rodless chamber, and the working area of ​​the rod chamber are determined. The driving force of the cylinder is then obtained through the force balance formula of the load of the valve-controlled asymmetric hydraulic cylinder system. The force balance formula for the load of the valve-controlled asymmetric hydraulic cylinder system is: In the formula, Let be the equivalent total mass of the piston rod and the load. The second derivative of the displacement. The pressure in the rodless chamber of the hydraulic cylinder. For the rod chamber pressure of the hydraulic cylinder, This refers to the working area of ​​the rodless chamber of the hydraulic cylinder. This refers to the working area of ​​the rod chamber of the hydraulic cylinder. For the load spring stiffness, For piston rod displacement, This is the load damping coefficient. The first derivative of the displacement. For the equivalent external load force and its unknown dynamic disturbance, This is the driving force for the hydraulic cylinder.

4. The method as described in claim 3, characterized in that, The steps of determining the corresponding rodless chamber working flow rate and rod chamber working flow rate based on the pressure of the rodless chamber of the hydraulic cylinder, the pressure of the rod chamber of the hydraulic cylinder, the oil supply pressure of the electro-hydraulic servo system, the oil return pressure of the electro-hydraulic servo system, the total gain coefficient of the electro-hydraulic servo valve, the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber of the cylinder, and the working volume of the rod chamber of the cylinder include: The working flow rates of the rodless chamber and the rod chamber are obtained by using the servo valve flow continuity formula based on the pressure of the rodless chamber of the hydraulic cylinder, the pressure of the rod chamber of the hydraulic cylinder, the oil supply pressure of the electro-hydraulic servo system, and the total gain coefficient of the electro-hydraulic servo valve. The formula for the continuity of the servo valve flow rate is: In the formula, For symbolic functions, The working flow rate of the rodless cavity, For the working flow rate of the rod cavity, Provide oil pressure for the electro-hydraulic servo system. For the control input signal of the servo valve, k t This refers to the overall gain coefficient of the servo valve. Based on the internal and external leakage coefficients of the cylinder, the external leakage coefficient of the cylinder, the elastic modulus of the hydraulic oil, the working volume of the rodless chamber of the cylinder, and the working volume of the rod chamber of the cylinder, the working flow rate of the rodless chamber and the working flow rate of the rod chamber are obtained through the flow continuity formula of the asymmetric hydraulic cylinder. The flow continuity formula for the asymmetric hydraulic cylinder is: In the formula, This represents the internal leakage coefficient of the hydraulic cylinder. This is the external leakage coefficient of the hydraulic cylinder. The elastic modulus of hydraulic oil. The working volume of the rodless chamber of the hydraulic cylinder. The working volume of the rod chamber of the hydraulic cylinder. and They are respectively and The time derivative; and They are respectively and The time derivative.

5. The method as described in claim 4, characterized in that, The step of constructing a third-order state-space model of the electro-hydraulic servo system based on the cylinder driving force, the working flow rate of the rodless chamber, the working flow rate of the rod chamber, and the state variables of the electro-hydraulic servo system includes: Based on the hydraulic cylinder driving force, the working flow rate of the rodless chamber, the working flow rate of the rod chamber, and the state variables of the electro-hydraulic servo system, a third-order state space model of the electro-hydraulic servo system is constructed using a preset vector formula. The preset vector formula is: In the formula, This represents the internal leakage coefficient of the hydraulic cylinder. This is the external leakage coefficient of the hydraulic cylinder. The elastic modulus of hydraulic oil. This is the effective stroke of the piston rod. This is the initial position of the piston rod. The derivative of the hydraulic cylinder driving force. , and For state vectors, , and State vector , and Time derivative, and for , and time t The function.

6. The method as described in claim 5, characterized in that, The step of obtaining multiple synchronization identification parameters for the extended system based on the third-order state-space model of the electro-hydraulic servo system includes: Based on the third-order state-space model of the electro-hydraulic servo system, multiple synchronous identification parameter extension systems are obtained through the hydraulic system motion balance formulas corresponding to multiple synchronous identification parameters. The multiple synchronous identification parameters include the equivalent total mass of the piston rod and the load, the load damping coefficient, the equivalent external load force and its unknown dynamic disturbance. The multiple synchronous identification parameter extension systems include the equivalent total mass extension system of the piston rod and the load, the load damping coefficient extension system, and the equivalent external load force and its unknown dynamic disturbance extension system. The hydraulic system motion balance formulas corresponding to multiple synchronous identification parameters are as follows: In the formula, For speed, For acceleration, For the driving force of the hydraulic cylinder, , and They are respectively , and Time derivative, The reciprocal of the load mass. For the extended system of equivalent total mass of piston rod and load, For load damping coefficient extended system, It is an extended system for equivalent external load force and its unknown dynamic disturbance.

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