Control method and device of hydraulic actuating mechanism, electronic equipment and storage medium

Abstract

The invention discloses a control method and device of a hydraulic actuator, electronic equipment and a storage medium, and the method comprises the steps: carrying out extension state prediction based on an obtained control input signal at a current sampling moment and displacement detection information, and obtaining a predicted extension state at the current sampling moment; the prediction extension state comprises a displacement state quantity, a speed state quantity, an acceleration state quantity and a random friction interference state quantity; performing extension state prediction at a plurality of future moments based on the prediction extension state at the current sampling moment to obtain a prediction extension state track; determining a target function taking a control input signal sequence corresponding to the prediction time domain as a variable based on the prediction extension state track and the expected displacement track, and minimizing the target function to obtain a target control input signal at each future moment; and controlling the hydraulic actuating mechanism to move based on the target control input signal at each future moment. According to the invention, the anti-interference capability and robustness of motion control of the hydraulic actuating mechanism are improved.

Description

Technical Field

[0001] This application relates to the field of transportation equipment assembly control technology, specifically to a control method, device, electronic equipment and storage medium for a hydraulic actuator. Background Technology

[0002] Containers are widely used as a means of transportation in modern industry. Their corrugated side panels feature a trapezoidal interface design, which improves rigidity and stability while reducing weight and cost. However, the flexibility, uneven surface, and other interferences during assembly of the corrugated side panels significantly increase the difficulty of accurately positioning them onto the bottom beam.

[0003] Electro-hydraulic servo systems (EHSS) are widely used in industrial fields. They can be used to flexibly position corrugated side plates during container assembly. In this flexible positioning process, the hydraulic actuator in the EHSS is crucial for correcting the deviation between the corrugated side plate and the bottom beam. Therefore, how to accurately control the hydraulic actuator has become an urgent problem to be solved. Summary of the Invention

[0004] To address the problems of the prior art, this application provides a control method, apparatus, electronic device, and storage medium for a hydraulic actuator. The technical solution is as follows: On the one hand, a control method for a hydraulic actuator is provided, the method comprising: Acquire the control input signal at the current sampling time, and the displacement detection information of the hydraulic actuator at the current sampling time; Based on the control input signal and the displacement detection information, an extended state prediction is performed to obtain the predicted extended state at the current sampling time; the predicted extended state includes displacement state quantity, velocity state quantity, acceleration state quantity, and random friction disturbance state quantity; Based on the predicted extended state at the current sampling time, multiple future extended state predictions are performed to obtain the predicted extended state trajectory; the predicted extended state trajectory represents the predicted extended state of the hydraulic actuator at each of the future times. Based on the predicted extended state trajectory and the expected displacement trajectory, an objective function is determined with the control input signal sequence corresponding to the predicted time domain as the variable, and the objective function is minimized to obtain the target control input signal at each of the future times; The hydraulic actuator is controlled to move based on the target control input signals at each of the future times.

[0005] In some implementations, the step of performing extended state prediction based on the control input signal and the displacement detection information to obtain the predicted extended state at the current sampling time includes: Based on the control input signal and the initial extended state, the initial predicted extended state is determined; the initial extended state includes the displacement state quantity, the velocity state quantity, the acceleration state quantity, and the random friction disturbance state quantity. Based on the initial predicted extended state and the output coefficient matrix, the initial predicted displacement is determined; Based on the deviation between the displacement detection information and the initial predicted displacement, the initial expansion state is adjusted until a preset convergence condition is met, thereby obtaining the predicted expansion state at the current sampling time.

[0006] In some implementations, the step of predicting extended states at multiple future times based on the predicted extended state at the current sampling time to obtain the predicted extended state trajectory includes: Based on the predicted extended state at the current sampling time, the predicted extended state at each future time is determined sequentially using a state space model; the state space model is used to describe the mapping relationship between the predicted extended state at the previous time, the changes in the control input signal and random friction interference, and the predicted extended state at the next time. The predicted extended state at each future time is obtained based on the predicted extended states of each future time prior to the future time and the predicted extended state at the current sampling time.

[0007] In some implementations, determining the objective function, which uses the control input signal sequence corresponding to the predicted time domain as a variable, based on the predicted extended state trajectory and the desired displacement trajectory includes: For each moment in the prediction time domain, the product of the prediction extended state corresponding to that moment in the prediction extended state trajectory and the output coefficient matrix is ​​determined to obtain the prediction displacement at each moment in the prediction time domain. The difference between the predicted displacement at a first number of times in the prediction time domain and the expected displacement at the corresponding times in the expected displacement trajectory is determined to obtain a first displacement deviation matrix; the first number of times are times other than the end time of the prediction time domain. The difference between the predicted displacement at the end time of the predicted time domain and the expected displacement at the corresponding time in the expected displacement trajectory is determined to obtain the second displacement deviation matrix; The objective function is obtained based on the first displacement deviation matrix, the second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain.

[0008] In some implementations, obtaining the objective function based on the first displacement deviation matrix, the second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain includes: The first function term is determined based on the product of the first error weight matrix and the first displacement deviation matrix; The second function term is determined based on the product of the second error weight matrix and the second displacement deviation matrix; The third function term is determined based on the product of the control input weight matrix and the control input signal sequence corresponding to the prediction time domain. The target function is obtained by summing the first function term, the second function term, and the third function term.

[0009] In some embodiments, controlling the movement of the hydraulic actuator based on the target control input signal at each of the future times includes: Acquire the target control input signals of the preset number of future times that are closest to the current sampling time; The hydraulic actuator is controlled to move sequentially based on the preset number of target control input signals for future times.

[0010] In some embodiments, the method further includes: When controlling the hydraulic actuator to move based on the target control input signal of the last future moment among the preset number of future moments, the target control input signal of the last future moment is used as the control input signal of the current sampling moment, and the control method of the hydraulic actuator is executed.

[0011] On the other hand, a control device for a hydraulic actuator is provided, the device comprising: The input signal acquisition module is used to acquire the control input signal at the current sampling time, as well as the displacement detection information of the hydraulic actuator at the current sampling time; The current extended state prediction module is used to predict the extended state based on the control input signal and the displacement detection information to obtain the predicted extended state at the current sampling time; the predicted extended state includes displacement state quantity, velocity state quantity, acceleration state quantity and random friction disturbance state quantity; The future extended state prediction module is used to predict the extended state at multiple future times based on the predicted extended state at the current sampling time, and obtain the predicted extended state trajectory; the predicted extended state trajectory represents the predicted extended state of the hydraulic actuator at each of the future times. The future control input determination module is used to determine an objective function with the control input signal sequence corresponding to the predicted time domain as a variable based on the predicted extended state trajectory and the expected displacement trajectory, and to minimize the objective function to obtain the target control input signal at each of the future times; The motion control module is used to control the motion of the hydraulic actuator based on the target control input signals at each of the future times.

[0012] In some implementations, the current extended state prediction module includes: An initial extended state determination module is used to determine an initial predicted extended state based on the control input signal and the initial extended state; the initial extended state includes the displacement state quantity, the velocity state quantity, the acceleration state quantity, and the random friction disturbance state quantity; The initial predicted displacement determination module is used to determine the initial predicted displacement based on the initial predicted extended state and the output coefficient matrix; An extended state correction module is used to adjust the initial extended state based on the deviation between the displacement detection information and the initial predicted displacement until a preset convergence condition is met, thereby obtaining the predicted extended state at the current sampling time.

[0013] In some implementations, the future extended state prediction module is specifically used to: determine the predicted extended state at each future time sequentially using a state space model based on the predicted extended state at the current sampling time; the state space model is used to describe the mapping relationship between the predicted extended state at the previous time, the changes in the control input signal and random friction interference, and the predicted extended state at the next time. The predicted extended state at each future time is obtained based on the predicted extended states of each future time prior to the future time and the predicted extended state at the current sampling time.

[0014] In some implementations, the future control input determination module includes: The first determining module is used to determine, for each time in the prediction time domain, the product of the prediction extended state corresponding to the time in the prediction extended state trajectory and the output coefficient matrix, so as to obtain the prediction displacement at each time in the prediction time domain. The first displacement deviation determination module is used to determine the difference between the predicted displacement at a first number of times in the prediction time domain and the expected displacement at the corresponding time in the expected displacement trajectory, and to obtain a first displacement deviation matrix; the first number of times are times other than the end time of the prediction time domain. The second displacement deviation determination module is used to determine the difference between the predicted displacement at the end time of the prediction time domain and the expected displacement corresponding to the expected displacement trajectory at the corresponding time, and to obtain the second displacement deviation matrix. The objective function construction module is used to obtain the objective function based on the first displacement deviation matrix, the second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain.

[0015] In some implementations, the objective function construction module is specifically used to: determine a first function term based on the product of a first error weight matrix and a first displacement deviation matrix; determine a second function term based on the product of a second error weight matrix and a second displacement deviation matrix; determine a third function term based on the product of a control input weight matrix and the control input signal sequence corresponding to the prediction time domain; and sum the first function term, the second function term, and the third function term to obtain the objective function.

[0016] In some embodiments, the motion control module includes: The acquisition module is used to acquire the target control input signals of the next preset number of future times that are closest to the current sampling time; The motion control submodule is used to control the motion of the hydraulic actuator sequentially based on the preset number of target control input signals at future times.

[0017] In some embodiments, the apparatus further includes: The sampling time determination module is used to control the movement of the hydraulic actuator based on the target control input signal of the last future time among the preset number of future times, and to use the target control input signal of the last future time as the control input signal of the current sampling time, and to execute the control method of the hydraulic actuator.

[0018] On the other hand, an electronic device is provided, including a processor and a memory, wherein the memory stores at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement a control method for a hydraulic actuator according to any of the above aspects.

[0019] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored therein, the at least one instruction or the at least one program being loaded and executed by a processor to implement the control method of the hydraulic actuator of any of the above aspects.

[0020] On the other hand, a computer program product is provided, including a computer program that, when executed by a processor, implements a control method for a hydraulic actuator according to any of the above aspects.

[0021] This application embodiment acquires the control input signal at the current sampling time and the displacement detection information of the hydraulic actuator at the current sampling time, and performs extended state prediction based on the control input signal and displacement detection information at the current sampling time to obtain the predicted extended state at the current sampling time. The predicted extended state includes displacement state quantity, velocity state quantity, acceleration state quantity, and random friction disturbance state quantity. Then, based on the predicted extended state at the current sampling time, multiple future time-times of extended state prediction are performed to obtain the predicted extended state trajectory. The predicted extended state trajectory represents the predicted extended state of the hydraulic actuator at each of the future time times. Based on the predicted extended state trajectory and the expected displacement trajectory, an objective function is determined with the control input signal sequence corresponding to the prediction time domain as the variable. The objective function is minimized to obtain the target control input signal at each of the future time times. Based on the target control input signal at each of the future time times, the movement of the hydraulic actuator is controlled, thereby improving the anti-interference capability and robustness of the hydraulic actuator's motion control. It can achieve precise control of the clamp connected to the output end of the hydraulic actuator, and thus achieve precise positioning of the corrugated side plate on the bottom beam during the assembly of the container corrugated side plate. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of a fixture for container assembly provided in an embodiment of this application; Figure 2 This is a schematic diagram of a valve-controlled asymmetric hydraulic cylinder provided in an embodiment of this application; Figure 3 This is a schematic flowchart of a control method for a hydraulic actuator provided in an embodiment of this application; Figure 4 This is a schematic diagram of the system control framework for implementing the control method of the hydraulic actuator provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of a control device for a hydraulic actuator provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0026] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0027] To enable any person skilled in the art to implement and use this application, the following description is provided. In this description, details are set forth for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be implemented without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0028] Containers are widely used as transportation tools in modern industry. Their corrugated side panels employ a trapezoidal interface design, which improves rigidity and stability while reducing weight and cost. However, the flexibility, uneven surface, and other interferences during assembly significantly increase the difficulty of accurately positioning the corrugated side panels onto the bottom beam. Currently, automated flexible positioning of the corrugated side panels during container assembly can be achieved using fixtures including electro-hydraulic servo systems, such as… Figure 1 The diagram shows a fixture 100 used in the container assembly process, which includes a hydraulic actuator 101 of the EHSS. In controlling the fixture 100 to perform automated flexible positioning of the corrugated side panels, the hydraulic actuator 101 is crucial for correcting the deviation between the corrugated side panels and the bottom beam. Therefore, how to accurately control the hydraulic actuator to precisely position the corrugated side panels onto the bottom beam is a problem that urgently needs to be solved.

[0029] In the process of realizing this invention, it was found that in the process of automated flexible positioning of corrugated side plates, factors such as uneven mass distribution, edge defects, and changes in clamping points can lead to unknown and time-varying friction. This unknown and time-varying friction interference has an adverse effect on the precise control of the hydraulic actuator in the EHSS.

[0030] In view of this, embodiments of this application provide a control method for a hydraulic actuator to cope with the aforementioned unknown and time-varying frictional interference, thereby improving the anti-interference capability and robustness of the motion control of the hydraulic actuator. This enables precise control of the clamp connected to the output end of the hydraulic actuator, and thus achieves precise positioning of the corrugated side panel onto the bottom beam during the assembly of the container corrugated side panel. The control method for the hydraulic actuator of this application embodiment will be described in detail below.

[0031] Before describing in detail the control method of the hydraulic actuator in the embodiments of this application, the hydraulic actuator in the embodiments of this application will be introduced first.

[0032] The core actuator for automated flexible positioning of the corrugated side plate is a valve-controlled asymmetric hydraulic cylinder, which is the hydraulic actuator in the embodiments of this application, such as... Figure 2 As shown, where, u The input signal for the proportional valve, also known as the control input signal, y For hydraulic cylinder displacement output, The area of ​​the rodless chamber piston is... The piston area of ​​the rod chamber. m Let be the equivalent total mass of the slider and the load. To supply hydraulic oil pressure, The pressure in the rodless cavity, For the pressure in the rod chamber, The volumetric flow rate of the rodless cavity. Q2 represents the volumetric flow rate of the rod-shaped cavity. For Figure 2 The hydraulic actuator, by controlling the position of the proportional valve core, can make the flow rates of hydraulic oil into the rodless chamber and the rod chamber different, thereby creating a pressure difference between the two chambers, driving the hydraulic cylinder slider to move, and thus controlling the movement of the hydraulic actuator.

[0033] Please see Figure 3 The diagram illustrates a flow chart of a control method for a hydraulic actuator according to an embodiment of this application. It should be noted that while this specification provides the operational steps described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive methods. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only possible execution order. In actual system or product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as shown... Figure 3 As shown, the control method for this hydraulic actuator may include: Step S301: Obtain the control input signal at the current sampling time, and the displacement detection information of the hydraulic actuator at the current sampling time.

[0034] The control input signal at the current sampling time refers to the proportional valve input signal. u This can characterize the opening size of the proportional valve. The displacement detection information of the hydraulic actuator at the current sampling moment characterizes the displacement output of the hydraulic actuator at the current sampling moment. y In other words, the actual displacement of the hydraulic actuator at the current sampling moment can be detected by a displacement sensor.

[0035] Step S303: Based on the control input signal and the displacement detection information, perform extended state prediction to obtain the predicted extended state at the current sampling time. The predicted extended state includes displacement state quantity, velocity state quantity, acceleration state quantity and random friction disturbance state quantity.

[0036] In this embodiment of the application, four state quantities are used to more accurately characterize the state of the hydraulic actuator. The displacement state quantity can be fed back in real time by a displacement sensor, while the velocity state quantity, acceleration state quantity, and random friction disturbance state quantity are predicted state quantities. The random friction disturbance state quantity can characterize the unknown and time-varying friction disturbance under the corresponding state.

[0037] In some implementations, step S303 may include the following: Based on the control input signal and the initial extended state, the initial predicted extended state is determined; the initial extended state includes the displacement state quantity, the velocity state quantity, the acceleration state quantity, and the random friction disturbance state quantity. Based on the initial predicted extended state and the output coefficient matrix, the initial predicted displacement is determined; Based on the deviation between the displacement detection information and the initial predicted displacement, the initial expansion state is adjusted until a preset convergence condition is met, thereby obtaining the predicted expansion state at the current sampling time.

[0038] Specifically, the following formula can be used to predict the extended state at the current sampling time:

[0039] in, It represents the initial extended state, which consists of displacement state quantities, velocity state quantities, acceleration state quantities, and random friction disturbance state quantities; Indicates the initial predicted extended state; This represents the output coefficient matrix. ; y This indicates displacement detection information; Indicates the initial predicted displacement; This represents the gain matrix, which can be used to control the convergence speed. This indicates the predicted extension state at the current sampling time.

[0040] in, The system matrix can describe how the various state variables within the system interact and evolve. The input matrix can describe how the control input signal u affects the system state.

[0041] in: , , , in, , , , , , , , , , , , .

[0042] in, This represents the effective bulk modulus of elasticity of the hydraulic actuator. Indicates the coefficient of viscous friction. Indicates the internal leakage coefficient. Indicates the valve flow coefficient. Indicates the density of hydraulic oil. Indicates the valve orifice area gradient. This represents flow gain. It should be noted that the bold letters in the embodiments of this application represent matrices or vectors.

[0043] In specific implementation, the gain matrix It can be designed based on the pole placement method to achieve a preset convergence rate. For example, the gain matrix... It can be obtained through the following formula:

[0044] in, Indicates the pole location of the control system.

[0045] The preset convergence condition can be that the deviation reaches a preset minimum deviation threshold, or the difference between two adjacent deviations reaches a difference threshold.

[0046] The above implementation method predicts the extended state in real time and then continuously approximates the real state through prediction-correction, thereby estimating the internal states and random frictional disturbances in the hydraulic system that cannot be directly measured by sensors in real time. This provides more accurate system state information for subsequent control, which helps to improve the anti-interference ability and accuracy of control.

[0047] Step S305: Based on the predicted extended state at the current sampling time, predict the extended state at multiple future times to obtain the predicted extended state trajectory. The predicted extended state trajectory represents the predicted extended state of the hydraulic actuator at each of the future times.

[0048] This application incorporates the predicted extended state at the current sampling time into Model Predictive Control (MCP). By predicting the extended state at multiple future moments in the prediction time domain based on the predicted extended state at the current sampling time, the predicted extended state trajectory is obtained. The prediction time domain includes the current sampling time and multiple future moments after the current sampling time.

[0049] In some implementations, step S305 may include: determining the predicted extended state of each future time sequentially using a state-space model based on the predicted extended state at the current sampling time; the state-space model is used to describe the mapping relationship between the predicted extended state of the previous time, the changes in the control input signal and random friction interference, and the predicted extended state of the next time; wherein the predicted extended state of each future time is obtained based on the predicted extended states of each future time before the future time and the predicted extended state at the current sampling time.

[0050] Specifically, the state-space model of a hydraulic actuator can be represented in the following form:

[0051] in, Indicates the current sampling time. +1 indicates the next future time after the current sampling time; , , , .

[0052] in, This represents the discrete time step, such as 0.005s; , and The calculation can be obtained by referring to the foregoing relevant descriptions of the embodiments of this application; This indicates changes due to random frictional disturbances; the above-mentioned express Predicted extended state at time step express Predicted extended state at time +1.

[0053] Using the above state-space model to predict the time domain If we perform time-by-time extended state prediction for each future time, then... The predicted extended state for each future time point is as follows:

[0054] Step S307: Based on the predicted extended state trajectory and the expected displacement trajectory, determine the objective function with the control input signal sequence corresponding to the predicted time domain as the variable, and minimize the objective function to obtain the target control input signal at each of the future times.

[0055] Specifically, the control input signal u of the state-space model is used as an optimizable variable, and by adjusting... u ( k ), u ( k +1),…,u ( k + This allows the future state to approximate the desired displacement trajectory, thereby obtaining a sequence of control input signals in the predictive time domain, which includes the target control input signals at each future time.

[0056] In some implementations, step S309 may include: For each moment in the prediction time domain, the product of the prediction extended state corresponding to that moment in the prediction extended state trajectory and the output coefficient matrix is ​​determined to obtain the prediction displacement at each moment in the prediction time domain. The difference between the predicted displacement at a first number of times in the prediction time domain and the expected displacement at the corresponding times in the expected displacement trajectory is determined to obtain a first displacement deviation matrix; the first number of times are times other than the end time of the prediction time domain. The difference between the predicted displacement at the end time of the predicted time domain and the expected displacement at the corresponding time in the expected displacement trajectory is determined to obtain the second displacement deviation matrix; The objective function is obtained based on the first displacement deviation matrix, the second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain.

[0057] Specifically, for predicting the time domain At a future moment, the aforementioned first displacement deviation matrix can be expressed as follows:

[0058] The second displacement deviation matrix mentioned above can be expressed as:

[0059] in, This indicates the predicted displacement.

[0060] Furthermore, based on the aforementioned first displacement deviation matrix, second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain... This allows us to construct the objective function to be optimized.

[0061] For example, obtaining the objective function based on the first displacement deviation matrix, the second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain may include: The first function term is determined based on the product of the first error weight matrix and the first displacement deviation matrix; The second function term is determined based on the product of the second error weight matrix and the second displacement deviation matrix; The third function term is determined based on the product of the control input weight matrix and the control input signal sequence corresponding to the prediction time domain. The target function is obtained by summing the first function term, the second function term, and the third function term.

[0062] Specifically, the first and second function terms measure the deviation between the system output and the desired trajectory at future time steps, reflecting the trajectory tracking error; the third function term measures the magnitude and rate of change of the control input signal, avoiding excessive or abrupt changes in the control quantity, reflecting energy consumption. The first and second error weight matrices can be used to adjust the importance of errors at different time steps, and the control input weight matrix can be used to adjust the input energy consumption of the control quantity. For example, if a more aggressive control is desired, the control input weight can be decreased; if smoother control is desired, the control input weight can be increased.

[0063] For example, the objective function can be expressed as follows:

[0064] in, Describe the objective function. The variable to be optimized; Q This represents the first error weight matrix, including time steps. k At that time The first error weight; R This represents the second error weight matrix, including time steps. The second error weight; F This represents the control input weight matrix, including time intervals. k At that time The control input weights.

[0065] Furthermore, by minimizing the above objective function J ( ), which can be used to obtain the hydraulic actuator in Target control input signal at a future time u .

[0066] For example, to achieve a balance between response time and error, a Non-dominated Sorting Genetic Algorithm II (NSGA-II) can be used to determine the appropriate prediction time domain. N p The first error weight, second error weight, and control input weight parameters in the aforementioned objective function can specifically be used to set two optimization objectives for NSGA-II: Objective 1 is to minimize the rise time, where the rise time reflects the system response speed; Objective 2 is to minimize the aforementioned objective function. In specific implementations, the embodiments of this application... It can be set to 11, with the first error weight being 657784007, the second error weight being 807124256, and the control input weight being 52688890.

[0067] Step S309: Based on the target control input signals at each of the future times, control the movement of the hydraulic actuator.

[0068] Specifically, when each future moment arrives, the target control input signal u of the corresponding future moment can be used to control the position of the proportional valve core, so that the flow rate of hydraulic oil flowing into the rodless chamber and the rod chamber is different, thereby generating a pressure difference in the two chambers, driving the slider of the hydraulic actuator to move, and then driving the fixture to move, so as to accurately position the corrugated side plate onto the bottom beam during the assembly of the container corrugated side plate.

[0069] In some implementations, step S309 may include: Acquire the target control input signals of the preset number of future times that are closest to the current sampling time; The hydraulic actuator is controlled to move sequentially based on the preset number of target control input signals for future times.

[0070] Specifically, from Obtain the target control input signal of the preset number of future moments closest to the current sampling moment from the future moments. For example, obtain the target control input signal of the 3 future moments closest to the current sampling moment, and then control the movement of the hydraulic actuator based on the target control input signal of the 3 future moments in sequence.

[0071] The preset quantity can be set based on the external environment of the hydraulic actuator. Generally, the greater the external environmental interference, the smaller the preset quantity can be set to ensure control accuracy; conversely, the smaller the external environmental interference, the larger the preset quantity can be set to improve response speed while ensuring control accuracy.

[0072] The above implementation method controls the movement of the hydraulic actuator by using a target control input signal based on a preset number of future times closest to the current sampling time, which can improve the response speed while ensuring control accuracy.

[0073] In some embodiments, the method may further include: when controlling the hydraulic actuator to move based on the target control input signal of the last future moment among the preset number of future moments, using the target control input signal of the last future moment as the control input signal of the current sampling moment, and executing the control method of the hydraulic actuator.

[0074] Specifically, when controlling the movement of the hydraulic actuator based on the target control input signal of the last future moment among a preset number of future moments, the last future moment can be used as the current sampling moment, and then the aforementioned steps S301 to S309 can be executed cyclically to achieve more stable and precise control.

[0075] To facilitate understanding of the technical solutions in the embodiments of this application, the following is combined with... Figure 4 The system control framework shown is illustrated by example. Figure 4 As shown, precise control of the hydraulic actuator is achieved through the cooperation of ESO (Extended State Observer) and MPC (Model Predictive Control). The ESO can be used to execute the aforementioned steps S301 to S303 of the embodiments of this application to achieve real-time estimation of random friction disturbances, and the estimation results are incorporated into the MPC. The MPC can be used to execute the aforementioned steps S305 to S309 of the embodiments of this application, thereby improving the response speed, anti-interference ability and robustness to load changes of the hydraulic actuator control, providing precise control for the intelligent container assembly system, and realizing the precise positioning of the corrugated side plate on the bottom beam.

[0076] Corresponding to the control methods of hydraulic actuators provided in the above embodiments, this application also provides a control device for hydraulic actuators. Since the control device for hydraulic actuators provided in this application corresponds to the control methods for hydraulic actuators provided in the above embodiments, the implementation methods of the aforementioned control methods for hydraulic actuators are also applicable to the control device for hydraulic actuators provided in this embodiment, and will not be described in detail in this embodiment.

[0077] Please see Figure 5 The diagram shows a structural schematic of a control device for a hydraulic actuator provided in an embodiment of this application. This device has the function of implementing the control method for the hydraulic actuator described in the above-described method embodiments. This function can be implemented by hardware or by hardware executing corresponding software. Figure 5 As shown, the control device 500 of the hydraulic actuator may include: The input signal acquisition module 510 is used to acquire the control input signal at the current sampling time, and the displacement detection information of the hydraulic actuator at the current sampling time; The current extended state prediction module 520 is used to predict the extended state based on the control input signal and the displacement detection information to obtain the predicted extended state at the current sampling time; the predicted extended state includes displacement state quantity, velocity state quantity, acceleration state quantity and random friction disturbance state quantity; The future extended state prediction module 530 is used to predict the extended state at multiple future times based on the predicted extended state at the current sampling time, and obtain the predicted extended state trajectory; the predicted extended state trajectory represents the predicted extended state of the hydraulic actuator at each of the future times. The future control input determination module 540 is used to determine an objective function with the control input signal sequence corresponding to the predicted time domain as a variable based on the predicted extended state trajectory and the expected displacement trajectory, and to minimize the objective function to obtain the target control input signal at each of the future times; The motion control module 550 is used to control the motion of the hydraulic actuator based on the target control input signals at each of the future times.

[0078] In some embodiments, the current extended state prediction module 520 includes: An initial extended state determination module is used to determine an initial predicted extended state based on the control input signal and the initial extended state; the initial extended state includes the displacement state quantity, the velocity state quantity, the acceleration state quantity, and the random friction disturbance state quantity; The initial predicted displacement determination module is used to determine the initial predicted displacement based on the initial predicted extended state and the output coefficient matrix; An extended state correction module is used to adjust the initial extended state based on the deviation between the displacement detection information and the initial predicted displacement until a preset convergence condition is met, thereby obtaining the predicted extended state at the current sampling time.

[0079] In some implementations, the future extended state prediction module 530 is specifically used to: determine the predicted extended state at each future time sequentially using a state space model based on the predicted extended state at the current sampling time; the state space model is used to describe the mapping relationship between the predicted extended state at the previous time, the changes in the control input signal and random friction interference, and the predicted extended state at the next time. The predicted extended state at each future time is obtained based on the predicted extended states of each future time prior to the future time and the predicted extended state at the current sampling time.

[0080] In some embodiments, the future control input determination module 540 includes: The first determining module is used to determine, for each time in the prediction time domain, the product of the prediction extended state corresponding to the time in the prediction extended state trajectory and the output coefficient matrix, so as to obtain the prediction displacement at each time in the prediction time domain. The first displacement deviation determination module is used to determine the difference between the predicted displacement at a first number of times in the prediction time domain and the expected displacement at the corresponding time in the expected displacement trajectory, and to obtain a first displacement deviation matrix; the first number of times are times other than the end time of the prediction time domain. The second displacement deviation determination module is used to determine the difference between the predicted displacement at the end time of the prediction time domain and the expected displacement corresponding to the expected displacement trajectory at the corresponding time, and to obtain the second displacement deviation matrix. The objective function construction module is used to obtain the objective function based on the first displacement deviation matrix, the second displacement deviation matrix, and the control input signal sequence corresponding to the prediction time domain.

[0081] In some implementations, the objective function construction module is specifically used to: determine a first function term based on the product of a first error weight matrix and a first displacement deviation matrix; determine a second function term based on the product of a second error weight matrix and a second displacement deviation matrix; determine a third function term based on the product of a control input weight matrix and the control input signal sequence corresponding to the prediction time domain; and sum the first function term, the second function term, and the third function term to obtain the objective function.

[0082] In some embodiments, the motion control module 550 includes: The acquisition module is used to acquire the target control input signals of the next preset number of future times that are closest to the current sampling time; The motion control submodule is used to control the motion of the hydraulic actuator sequentially based on the preset number of target control input signals at future times.

[0083] In some embodiments, the device 500 further includes: The sampling time determination module is used to control the movement of the hydraulic actuator based on the target control input signal of the last future time among the preset number of future times, and to use the target control input signal of the last future time as the control input signal of the current sampling time, and to execute the control method of the hydraulic actuator.

[0084] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when implementing its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0085] This application also provides an electronic device, including a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement any of the hydraulic actuator control methods provided in the above method embodiments.

[0086] The methods and embodiments provided in this application can be executed on a computer terminal, server, or similar computing device. Figure 6 This is a hardware structure block diagram of an electronic device that operates a control method for a hydraulic actuator, as provided in an embodiment of this application. Figure 6 As shown, the internal structure of this electronic device may include, but is not limited to, a processor, a network interface, and a memory. The processor, network interface, and memory within the electronic device can be connected via a bus or other means, as illustrated in the embodiments of this specification. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0087] The processor (or CPU, Central Processing Unit) is the computing and control core of the computer device. The network interface may optionally include a standard wired interface or a wireless interface (such as Wi-Fi, mobile communication interface, etc.). The memory is the storage device in the computer device used to store programs and data. It is understood that the memory here can be a high-speed RAM storage device, or a non-volatile storage device, such as at least one disk storage device; optionally, it can also be at least one storage device located remotely from the aforementioned processor. The memory provides storage space, which stores the operating system of the electronic device, including but not limited to: Windows (an operating system), Linux (an operating system), Android (a mobile operating system), iOS (a mobile operating system), etc., which are not limited in this invention; and the storage space also stores one or more instructions suitable for being loaded and executed by the processor, which can be one or more computer programs (including program code). In the embodiments of this specification, the processor loads and executes one or more instructions stored in the memory to implement the control method of the hydraulic actuator provided in the above method embodiments.

[0088] This application also provides a computer-readable storage medium, which can be disposed in an electronic device to store at least one instruction or at least one program related to implementing a control method for a hydraulic actuator. The at least one instruction or at least one program is loaded and executed by the processor to implement any of the hydraulic actuator control methods provided in the above method embodiments.

[0089] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the hydraulic actuator control methods provided in the above-described method embodiments.

[0090] In the embodiments of this application, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0091] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0093] The control method, device, electronic device, and storage medium of a hydraulic actuator provided in the embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A control method of a hydraulic actuator, characterized by, The method comprises: obtaining a control input signal at a current sampling time and displacement detection information of the hydraulic actuator at the current sampling time; based on the control input signal and the displacement detection information, performing extended state prediction to obtain a predicted extended state at the current sampling time; the predicted extended state comprises a displacement state quantity, a velocity state quantity, an acceleration state quantity and a random friction disturbance state quantity; based on the predicted extended state at the current sampling time, performing extended state prediction for a plurality of future times to obtain a predicted extended state trajectory; the predicted extended state trajectory represents the predicted extended state of the hydraulic actuator at each of the future times; based on the predicted extended state trajectory and an expected displacement trajectory, determining a target function with the control input signal sequence corresponding to the prediction time domain as a variable, and minimizing the target function to obtain a target control input signal at each of the future times; based on the target control input signal at each of the future times, controlling the movement of the hydraulic actuator.

2. The method of claim 1, wherein, The method comprises: based on the control input signal and the displacement detection information, performing extended state prediction to obtain a predicted extended state at the current sampling time; the predicted extended state comprises a displacement state quantity, a velocity state quantity, an acceleration state quantity and a random friction disturbance state quantity; based on the control input signal and the initial extended state, determining an initial predicted extended state; the initial extended state comprises the displacement state quantity, the velocity state quantity, the acceleration state quantity and the random friction disturbance state quantity; based on the initial predicted extended state and the output coefficient matrix, determining an initial predicted displacement; 3. The method of claim 1, wherein, based on the deviation between the displacement detection information and the initial predicted displacement, adjusting the initial extended state until a preset convergence condition is met to obtain the predicted extended state at the current sampling time. The method comprises: based on the predicted extended state at the current sampling time, sequentially determining the predicted extended state at each of the future times by using a state space model; the state space model is used to describe the mapping relationship between the predicted extended state at the previous time, the control input signal and the random friction disturbance change and the predicted extended state at the next time; 4. The method of claim 1, wherein, wherein, the predicted extended state at each future time is obtained based on the predicted extended state at each of the future times before the future time and the predicted extended state at the current sampling time. The method comprises: for each time in the prediction time domain, determining the product of the predicted extended state corresponding to the time in the predicted extended state trajectory and the output coefficient matrix to obtain the predicted displacement at each time in the prediction time domain; determining the difference between the predicted displacement at the first number of times in the prediction time domain and the expected displacement corresponding to the respective time in the expected displacement trajectory to obtain a first displacement deviation matrix; the first number of times is the time other than the terminal time of the prediction time domain. determining a difference between a predicted displacement of an end time point of the prediction time domain and a corresponding expected displacement in the expected displacement trajectory at the corresponding time point, to obtain a second displacement deviation matrix; obtaining the target function based on the first displacement deviation matrix, the second displacement deviation matrix and a control input signal sequence corresponding to the prediction time domain.

5. The method of claim 4, wherein, The obtaining of the target function based on the first displacement deviation matrix, the second displacement deviation matrix and the control input signal sequence corresponding to the prediction time domain comprises: determining a first function item based on a product of a first error weight matrix and the first displacement deviation matrix; determining a second function item based on a product of a second error weight matrix and the second displacement deviation matrix; determining a third function item based on a product of a control input weight matrix and the control input signal sequence corresponding to the prediction time domain; summing the first function item, the second function item and the third function item to obtain the target function.

6. The method of claim 1, wherein, The control of the hydraulic actuator based on the target control input signal of each future time point comprises: obtaining target control input signals of a preset number of future time points closest to the current sampling time point; controlling the hydraulic actuator based on the target control input signals of the preset number of future time points in turn.

7. The method of claim 6, wherein, The method further comprises: when the hydraulic actuator is controlled based on the target control input signal of the last future time point in the preset number of future time points, taking the target control input signal of the last future time point as a control input signal of the current sampling time point and executing the control method of the hydraulic actuator.

8. A control device for a hydraulic actuator, characterized by comprising: The device comprises: an input signal acquisition module configured to acquire a control input signal of a current sampling time point and displacement detection information of the hydraulic actuator at the current sampling time point; a current extended state prediction module configured to perform extended state prediction based on the control input signal and the displacement detection information to obtain a predicted extended state of the current sampling time point; the predicted extended state comprises displacement state quantity, velocity state quantity, acceleration state quantity and random friction disturbance state quantity; a future extended state prediction module configured to perform extended state prediction of a plurality of future time points based on the predicted extended state of the current sampling time point to obtain a predicted extended state trajectory; the predicted extended state trajectory represents predicted extended states of the hydraulic actuator at the future time points; a future control input determination module configured to determine a target function with a control input signal sequence corresponding to a prediction time domain as a variable based on the predicted extended state trajectory and an expected displacement trajectory, and minimize the target function to obtain target control input signals of the future time points; a motion control module configured to control the motion of the hydraulic actuator based on the target control input signals of the future time points.

9. An electronic device, comprising: The hydraulic actuator control method according to any one of claims 1-7 is implemented by a processor loading and executing at least one instruction or at least one program stored in a memory including the processor and the memory.

10. A computer-readable storage medium, characterized in that, The hydraulic actuator control method according to any one of claims 1-7 is implemented by a processor loading and executing at least one instruction or at least one program stored in a computer readable storage medium.

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