Hydraulic anchor rod drilling machine global sliding mode displacement control method and system based on PSO and adaptive ESO

Abstract

The application provides a hydraulic anchor drill global sliding mode displacement control method and system based on PSO and adaptive ESO, and relates to the technical field of coal mine roadway supporting equipment control. The method comprises the following steps: obtaining state variables of a hydraulic anchor drill displacement system; constructing an adaptive extended state observer based on the state variables, estimating system total disturbance in real time, and outputting a total disturbance estimation value; constructing a pre-compensation type global sliding mode surface based on the state variables, and constructing a global sliding mode control law based on Lyapunov stability theory; introducing the total disturbance estimation value into the global sliding mode control law to construct a controller and output a control input variable; constructing a target function, optimizing and setting the controller parameters to obtain an optimal parameter combination; and applying the controller to the hydraulic anchor drill displacement system based on the optimal parameter combination to realize closed-loop control of displacement. The application enhances control precision and system robustness, and improves the safety and reliability of coal mine roadway supporting operations.

Description

Technical Field

[0001] This invention relates to the field of coal mine roadway support equipment control technology, and in particular to a global sliding mode displacement control method and system for hydraulic rock bolt drilling rigs based on PSO and adaptive ESO. Background Technology

[0002] In coal mine roadway support operations, hydraulic rock bolt drilling rigs serve as key actuators, and their displacement control accuracy directly impacts support quality and operational safety. Currently, hydraulic rock bolt drilling rig displacement systems commonly employ electro-hydraulic proportional valves and hydraulic cylinders as actuators and control elements, exhibiting characteristics such as nonlinearity, strong coupling, and susceptibility to external disturbances. Although some control methods have been applied to these systems, under actual operating conditions, the systems often face complex disturbances such as parameter perturbations, load changes, and unmodeled dynamics, making it difficult for traditional control strategies to achieve high-precision and robust displacement tracking.

[0003] In existing research, sliding mode control has attracted widespread attention due to its good robustness to parameter perturbations and external disturbances. However, traditional sliding mode control suffers from chattering, which limits its application in hydraulic systems; at the same time, control methods that rely on high-precision disturbance information are difficult to implement in engineering practice. Although extended state observers (ESOs) can be used for disturbance estimation, conventional ESOs have fixed gains, making it difficult to balance convergence speed and estimation accuracy when the system is dynamically changing, and their parameter tuning is complex, limiting their practicality.

[0004] Therefore, there is an urgent need to propose a displacement control method and system that can effectively suppress sliding mode chattering, achieve accurate disturbance estimation and simple control parameter tuning, and improve engineering applicability and control reliability while ensuring system response speed and control accuracy. Summary of the Invention

[0005] The purpose of this invention is to provide a global sliding form displacement control method and system for hydraulic rock bolt drilling rigs based on PSO and adaptive ESO. This method solves the problems of insufficient tracking accuracy, poor anti-disturbance capability, severe sliding form chattering, and difficulty in setting controller parameters in existing technologies under complex working conditions. It can enhance control accuracy and system robustness, thereby improving the safety and reliability of coal mine roadway support operations.

[0006] To achieve the above objectives, this invention provides a global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO, comprising the following steps: Step S1: Obtain the state variables of the hydraulic anchor drilling rig displacement system; Step S2: Construct an adaptive extended state observer based on the state variables to estimate the total system disturbance in real time and output the total disturbance estimate. Step S3: Construct a pre-compensated global sliding surface based on state variables, and construct a global sliding control law based on Lyapunov stability theory; Step S4: Introduce the total disturbance estimate into the global sliding mode control law, construct the controller, and output the control input variables; Step S5: Construct the objective function, optimize and tune the controller parameters, and obtain the optimal parameter combination; Step S6: Based on the optimal parameter combination, apply the controller constructed in step S4 to the displacement system of the hydraulic anchor drilling rig to achieve closed-loop control of the displacement.

[0007] Preferably, in step S2, constructing an adaptive extended state observer based on state variables specifically includes: definition State variables The estimated value, of which For index variables, , For displacement, Let the displacement be the estimated value; let the state estimation error be... Construct an adaptive strategy, the specific expression of which is: ; ; in, It is an adaptive gain function. For combination coefficients, It is an exponential function. It is a hyperbolic cosine function. Let be the coefficients of the hyperbolic cosine function, and ; Based on the adaptive strategy, an adaptive extended state observer is constructed, with the specific expression as follows: ; in, To control input variables, This is the estimated total disturbance. Displacement estimate The first-order time derivative, Speed ​​estimate The first-order time derivative, The actual control gain of the system The per-unit value.

[0008] Preferably, step S3 specifically includes: remember To track the signal, let the tracking estimation error be... Construct a pre-compensated sliding mode function The specific expression is: ; in, This is the error scaling factor for the pre-compensation sliding mode function, and , To track estimation error The first-order time derivative; Constructing a fast convergence function The specific expression is: ; in, For runtime, For frequency adjustment parameters; Based on pre-compensated sliding mode function and fast convergence function Constructing a pre-compensated global sliding surface The specific expression is: ; in, For pre-compensation sliding mode function The initial value; make , and To meet For odd numbers, based on Lyapunov stability theory, a global sliding mode control law is constructed, the specific expression of which is: ; in, To track the proportional coefficient of the differential term of the estimation error, To track signals The second-order time derivative, For pre-compensated global sliding surface Gain coefficient, For fast convergence function The first-order time derivative, This is the output variable of the global sliding mode control law.

[0009] Preferably, in step S4, the total disturbance estimate is introduced into the global sliding mode control law to construct the controller, the specific expression of which is: ; in, This is the estimated total disturbance. To control input variables.

[0010] Preferably, in step S5, the objective function is constructed using a particle swarm optimization algorithm. The specific expression is: ; ; ; ; ; ; ; in, The mean; Standard deviation; To track error indicators; To control energy indicators; For robustness indicators; For sliding mode chattering index; For overshoot indicators; To adjust time indicators; The system outputs the maximum value; This is a reference signal for displacement tracking. This refers to the actual settling time from startup to reaching steady state. For tracking error, and , Output variables for the system; for The first-order time differential.

[0011] Preferably, the control method ensures that the displacement output of the hydraulic anchor drilling rig displacement system remains stable within a finite time, and the specific expression for the convergence time is: ; in, Lyapunov function initial value, To shorten the convergence time, where are the positive definite coefficients of the Lyapunov function, and .

[0012] This invention also provides a global sliding mode displacement control system for hydraulic anchor drilling rigs based on PSO and adaptive ESO, employing the above-mentioned method, including: The data acquisition module is used to acquire the state variables of the hydraulic anchor drilling rig displacement system; The adaptive extended state observer module, connected to the data acquisition module, is used to construct an adaptive extended state observer based on state variables, estimate the total system disturbance in real time, and output the total disturbance estimate. The global sliding mode control module, connected to the data acquisition module, is used to construct a pre-compensated global sliding surface based on state variables and to construct a global sliding mode control law based on Lyapunov stability theory. The controller construction module is connected to the adaptive extended state observer module and the global sliding mode control module, respectively. It is used to introduce the total disturbance estimate into the global sliding mode control law, construct the controller, and output the control input variable. The parameter optimization module is connected to the adaptive extended state observer module, the global sliding mode control module, and the controller construction module, respectively, and is used to optimize and tune the controller parameters to obtain the optimal parameter combination. The control execution module, connected to the controller construction module, is used to apply the controller to the hydraulic anchor drilling rig displacement system based on the optimal parameter combination, thereby achieving closed-loop control of the displacement.

[0013] Preferably, the parameter optimization module uses the particle swarm optimization algorithm to construct an objective function with the goal of improving system control accuracy and response speed, and optimizes and tunes the controller parameters.

[0014] Therefore, the present invention employs the above-mentioned global sliding mode displacement control method and system for hydraulic anchor drilling rigs based on PSO and adaptive ESO, and the beneficial technical effects are as follows: (1) By constructing an adaptive extended state observer, this invention only requires tuning one parameter compared to the existing fixed gain ESO, which is more conducive to engineering practice; at the same time, it can realize adaptive adjustment of the gain, which can accelerate the convergence speed and improve the estimation accuracy, so that the displacement system can estimate the disturbance more quickly and accurately, thereby ensuring the high-quality implementation of support operations.

[0015] (2) This invention proposes a novel pre-compensated global sliding surface. Unlike existing sliding control methods, this sliding surface is constructed based on the tracking signal rather than the tracking error. It solves the chattering problem caused by the robust term of the sign function when dealing with disturbance estimation error, and also solves the problem of increased control complexity due to the use of adaptive law. At the same time, the total disturbance estimate is integrated into the sliding surface to pre-compensate the differential term, which simplifies the design process.

[0016] (3) The fast convergence function constructed in this invention has better convergence performance than the exponential function, thereby ensuring better global sliding mode robustness, enabling the system to stabilize in a finite time, and giving a clear convergence time expression.

[0017] (4) The present invention uses particle swarm optimization algorithm to optimize and tune the controller parameters. By designing an objective function that includes multiple dimensions such as tracking error, control energy, robustness, sliding mode chattering, overshoot and settling time, it ensures that the system can achieve better comprehensive control performance by using the optimal or suboptimal parameter combination.

[0018] (5) The method of the present invention has been demonstrated through simulation experiments that the displacement system of the hydraulic anchor drilling rig can achieve high-precision tracking of the reference signal without overshoot; at the same time, the control input is smooth and the amplitude is small, indicating that the method of the present invention can not only effectively avoid sliding mode chattering, but also achieve high-efficiency tracking performance with a small control amount. Attached Figure Description

[0019] Figure 1 The flowchart shows the global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO of the present invention. Figure 2 This is a graph showing the optimal fitness iteration curve during the PSO algorithm iteration process. Figure 3 This is a parameter iteration diagram during the PSO algorithm iteration process; Figure 4 This is a reference signal diagram for displacement tracking in the displacement system of a hydraulic anchor drilling rig. Figure 5 A graph showing the periodic external disturbances applied to the simulation. Figure 6 This is a comparison curve of the tracking error between the method of the present invention and comparative method 1; Figure 7 This is a comparison curve of the tracking error between the method of the present invention and comparative method 2; Figure 8 This is a comparison curve of the tracking error between the method of the present invention and comparative method 3; Figure 9 This is a comparison curve of the tracking error between the method of the present invention and the comparative method 4; Figure 10 This is a comparison curve of the control inputs of the method of the present invention and comparative method 1; Figure 11 This is a comparison curve of the control inputs of the method of the present invention and comparative method 2; Figure 12 This is a comparison curve of the control input between the method of the present invention and comparative method 3; Figure 13 This is a comparison curve of the control input between the method of the present invention and comparative method 4. Detailed Implementation

[0020] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0022] Example 1 like Figure 1As shown, the global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO includes the following steps: Step S1: Obtain the state variables of the hydraulic anchor drilling rig displacement system.

[0023] In this invention, the hydraulic cylinder and the electro-hydraulic proportional valve of the hydraulic anchor drilling rig displacement system are the displacement actuator and control actuator, respectively. The controller controls the displacement of the hydraulic cylinder by adjusting the opening of the electro-hydraulic proportional valve. This invention constructs a displacement system model by analyzing the dynamic characteristics of the hydraulic cylinder and the electro-hydraulic proportional valve, where the meanings of the main parameters are shown in Table 1.

[0024] Table 1. Main parameters of the displacement system model and their meanings

[0025] The specific expression for the dynamic characteristics of the flow rate of a hydraulic cylinder is as follows: .

[0026] Based on Newton's laws, the dynamic pressure equation for a hydraulic cylinder is derived, and its specific expression is as follows: .

[0027] The specific expression for the flow dynamic characteristics of an electro-hydraulic proportional valve is as follows: .

[0028] After rearranging the above formula, we get: ; in, For load pressure The first-order time derivative, For load displacement The first-order time derivative, For symbolic functions, For load displacement The second-order time derivative.

[0029] By introducing dead zone compensation technology, the valve core displacement is obtained. The specific expression is: .

[0030] Obtain the state variables of the hydraulic anchor drilling rig displacement system ,in For displacement, For speed, For acceleration, For index variables, and order , Construct a displacement system model, the specific expression of which is: ; ; ; ; in, for per-unit value, for The deviation value, This represents the actual control gain of the system. displacement The first-order time derivative, For speed The first-order time derivative, Indicates a disturbance.

[0031] Step S2: Construct an adaptive extended state observer (ESO) based on the state variables to estimate the total system disturbance in real time and output the estimated total disturbance value, specifically including: definition State variables The estimated value, of which For index variables, , For displacement, Let the displacement be the estimated value; let the state estimation error be... Construct an adaptive strategy, the specific expression of which is: ; ; in, It is an adaptive gain function. For combination coefficients, It is an exponential function. It is a hyperbolic cosine function. Let be the coefficients of the hyperbolic cosine function, and .

[0032] Based on the adaptive strategy, an adaptive extended state observer is constructed, with the specific expression as follows: ; in, To control input variables, This is the estimated total disturbance. Displacement estimate The first-order time derivative, Speed ​​estimate The first-order time derivative, The actual control gain of the system The per-unit value.

[0033] Compared with existing ESOs, the adaptive ESO constructed in this invention has the following advantages: only one needs to be tuned. This makes it more suitable for engineering practice; at the same time, addressing the poor estimation performance of fixed-gain ESOs, the adaptive ESO of this invention uses an adaptive gain function. Adaptive gain adjustment can accelerate convergence and improve estimation accuracy. Therefore, the adaptive ESO of this invention enables displacement systems to estimate disturbances more quickly and accurately, thereby ensuring high-quality implementation of support operations.

[0034] Step S3: Based on the state variables, construct a pre-compensated global sliding surface, and construct a global sliding mode control law based on Lyapunov stability theory, specifically including: remember To track the signal, let the tracking estimation error be... Construct a pre-compensated sliding mode function The specific expression is: ; in, This is the error scaling factor for the pre-compensation sliding mode function, and , To track estimation error The first-order time differential.

[0035] To ensure superior global sliding mode robustness, a fast convergence function is constructed. The specific expression is: ; in, For runtime, These are the frequency adjustment parameters.

[0036] Based on pre-compensated sliding mode function and fast convergence function Construct a pre-compensated global sliding surface The specific expression is: ; in, For pre-compensation sliding mode function The initial value.

[0037] make , and To meet For odd numbers, based on Lyapunov stability theory, a global sliding mode control law is constructed, the specific expression of which is: ; in, To track the proportional coefficient of the differential term of the estimation error, To track signals The second-order time derivative, For pre-compensated global sliding surface Gain coefficient, For fast convergence function The first-order time derivative, This is the output variable of the global sliding mode control law.

[0038] Unlike existing sliding mode control methods, the pre-compensated global sliding surface of this invention is based on Instead of tracking errors, this improvement addresses both the chattering problem caused by the robust term of the sign function when handling disturbance estimation errors and the increased control complexity resulting from the use of adaptive laws. Furthermore, it... Integration Pre-compensation of the differential term simplifies the design process; on the other hand, it constructs a function with convergence performance superior to the exponential function. This ensures better global sliding mode robustness.

[0039] Step S4: Introduce the total disturbance estimate into the global sliding mode control law, construct the controller, and output the control input variables.

[0040] The total disturbance estimate is incorporated into the global sliding mode control law to construct the controller, with the specific expression as follows: ; in, This is the estimated total disturbance. To control input variables.

[0041] It should be noted that the control input variables appearing in step S2 The control input variables output in step S4 They are the same physical quantity. In terms of the method flow, the controller output constructed in step S4... This will be used as input to the adaptive extended state observer in step S2 to achieve real-time estimation of the system state.

[0042] To verify the stability of the method of this invention, the following Lyapunov function was selected. : ; By differentiating the selected Lyapunov function and based on the global sliding mode control law constructed in step S3 and the controller constructed in step S4, the following can be derived: ; in, Lyapunov function The first-order time derivative, For pre-compensated global sliding surface The first-order time differential.

[0043] Combining Lyapunov functions It can be known that it exists. , making .

[0044] According to Lyapunov's stability theory, the system is asymptotically stable. Further analysis shows that the method of this invention enables the displacement output of the hydraulic anchor drilling rig displacement system to remain stable within a finite time, and the specific expression for the convergence time is: ; in, Lyapunov function initial value, To shorten the convergence time, where are the positive definite coefficients of the Lyapunov function, and .

[0045] Step S5: Construct the objective function, optimize and tune the controller parameters, and obtain the optimal parameter combination.

[0046] The control method proposed in this invention includes: , and The controller parameters, including those of the displacement system, directly affect the control performance of the system. To ensure superior control performance, a particle swarm optimization (PSO) algorithm is used to set a more suitable combination of parameters for the controller.

[0047] The objective function is constructed using the particle swarm optimization algorithm. The specific expression is: ; ; ; ; ; ; ; in, The mean; Standard deviation; To track error metrics and ensure they converge quickly; To control energy indicators and suppress the amplitude and fluctuation of control quantities; To provide robust indicators and prevent large errors and drastic control fluctuations; This is a sliding mode chattering index used to suppress the effects of chattering; It serves as an overshoot indicator, used to suppress overshoot; To adjust the time index in order to speed up the convergence time; The system outputs the maximum value; This is a reference signal for displacement tracking. This refers to the actual settling time from startup to reaching steady state. For tracking error, and , Output variables for the system; for The first-order time differential.

[0048] In particle swarm optimization (PSO) algorithms, the objective function provides directional guidance for particle motion. Particles adjust their direction by comparing the objective function value corresponding to their current position with the objective function values ​​corresponding to their individual best position and the swarm's best position. As iterations proceed, particles gradually cluster in regions with better objective function values. Based on this, the system can achieve better control performance using optimal or near-optimal parameter combinations.

[0049] Step S6: Based on the optimal parameter combination, apply the controller constructed in step S4 to the displacement system of the hydraulic anchor drilling rig to achieve closed-loop control of the displacement.

[0050] A global sliding form displacement control system for hydraulic anchor drilling rigs based on PSO and adaptive ESO is adopted, including the following: The data acquisition module is used to acquire the state variables of the hydraulic anchor drilling rig displacement system.

[0051] The adaptive extended state observer module, connected to the data acquisition module, is used to construct an adaptive extended state observer based on state variables, estimate the total system disturbance in real time, and output the total disturbance estimate.

[0052] The global sliding mode control module, connected to the data acquisition module, is used to construct a pre-compensated global sliding surface based on state variables and to construct a global sliding mode control law based on Lyapunov stability theory.

[0053] The controller construction module is connected to the adaptive extended state observer module and the global sliding mode control module, respectively. It is used to introduce the total disturbance estimate into the global sliding mode control law, construct the controller, and output the control input variable.

[0054] The parameter optimization module is connected to the adaptive extended state observer module, the global sliding mode control module, and the controller construction module, respectively, and is used to optimize and tune the controller parameters to obtain the optimal parameter combination.

[0055] The parameter optimization module employs a particle swarm optimization algorithm to construct an objective function with the goal of improving system control accuracy and response speed, and then optimizes and tunes the controller parameters.

[0056] The control execution module, connected to the controller construction module, is used to apply the controller to the hydraulic anchor drilling rig displacement system based on the optimal parameter combination, thereby achieving closed-loop control of the displacement.

[0057] To verify the effectiveness and superiority of the method of the present invention, a simulation experiment was conducted in the MATLAB environment in this embodiment.

[0058] In the PSO parameter optimization, the number of particles in the population is set to 30, the velocity weight is 0.6, the influence weight of the global optimal particle position is 2, and the influence weight of the historical optimal particle position is 2. To avoid excessively long runtime for the parameter optimization algorithm, the maximum number of termination iterations is set to 200. To accelerate the population evolution, initial values ​​and boundary ranges are set for the particles: , and The initial values ​​of the particles are 2, 10, and 2 respectively, and the boundary range of each particle is 10. .

[0059] like Figure 4 The diagram shown is a reference signal diagram for displacement tracking in the displacement system of a hydraulic anchor drilling rig. Figure 5 The figure shows the curve of the periodic external disturbance applied in the simulation. Other control parameters are set as follows: sampling period. .

[0060] like Figure 2 As shown, the fitness value gradually decreases with the increase of the number of iterations. The system achieves the optimal fitness in the 81st generation, indicating that the PSO algorithm can effectively search for a better combination of parameters.

[0061] like Figure 3 Showing , and The iterative change trend during the PSO algorithm iteration process, ultimately, , and The values ​​are 26.4, 2.2 and 5.2 respectively.

[0062] To further verify the superiority of the method of the present invention, this embodiment selects the following four existing control methods as comparative examples and conducts simulation comparison experiments under the same simulation conditions. The simulation results are as follows: Figures 6 to 13 As shown. The four existing control methods specifically include: (1) Comparison Method 1: Proportional-Integral-Derivative Controller, control law is: ; in, To track errors, for The first time derivative, This is the proportional gain coefficient. This is the integral gain coefficient. The differential gain coefficient, , , .

[0063] (2) Comparison Method 2: Sliding mode controller, the control law is: ; ; ; in, The sliding surface coefficient of the sliding mode controller. The switching gain coefficient of the sliding mode controller. The slope coefficient of the Sigmoid function. For the Sigmoid function, For the sliding surface variable, , , .

[0064] (3) Comparison Method 3: Active Disturbance Rejection Controller, control law is: ; It is estimated by the following linear extended observer: ; in, , , For the linearly extended observer gain parameter, The differential gain coefficient is the error coefficient. To estimate the gain coefficient for speed, , , , , .

[0065] (4) Comparison Method 4: Sliding mode controller based on linear extended observer, with the control law as follows: ; ; in, For displacement tracking reference signal The second-order time derivative, The sliding surface coefficients are for a sliding mode controller based on a linear extended observer. The gain coefficient of the sliding surface. The switching gain coefficients of the sliding mode controller based on the linear extended observer are... , , , The linear extended observer estimation was obtained using comparative method 3.

[0066] like Figures 6 to 9 As shown, compared with four existing control methods, the hydraulic anchor drilling rig displacement system using the method of this invention can quickly track the reference signal, and the tracking error rapidly converges to near zero, without any overshoot throughout the process. The results demonstrate that the method of this invention enables the displacement system to achieve overshoot-free and high-precision tracking of the reference signal, exhibiting excellent tracking performance.

[0067] like Figures 10 to 13 As shown, compared with the four existing control methods, the control input curve of the method of the present invention is smooth and has a small amplitude, without any drastic fluctuations or high-frequency oscillations. The results indicate that the method of the present invention can not only effectively avoid the sliding mode chattering problem, but also achieve efficient tracking performance with relatively low control energy, demonstrating good engineering applicability.

[0068] In summary, the simulation results verified the rationality and effectiveness of the method of the present invention, which can effectively improve the control performance of the displacement system of the hydraulic anchor drilling rig and provide technical support for the safety and reliability of coal mine roadway support operations.

[0069] Therefore, the present invention adopts the above-mentioned global sliding displacement control method and system for hydraulic anchor drilling rigs based on PSO and adaptive ESO, which solves the problems of insufficient tracking accuracy, poor anti-disturbance ability, severe sliding mode chattering, and difficulty in setting controller parameters in the existing technology under complex working conditions. It enhances the control accuracy and system robustness, and improves the safety and reliability of coal mine roadway support operations.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO, characterized in that, Includes the following steps: Step S1: Obtain the state variables of the hydraulic anchor drilling rig displacement system; Step S2: Construct an adaptive extended state observer based on the state variables to estimate the total system disturbance in real time and output the total disturbance estimate. Constructing an adaptive extended state observer based on state variables specifically includes: definition State variables The estimated value, of which For index variables, , For displacement, Let the displacement be the estimated value; let the state estimation error be... Construct an adaptive strategy, the specific expression of which is: ； ； in, It is an adaptive gain function. For combination coefficients, It is an exponential function. It is a hyperbolic cosine function. Let be the coefficients of the hyperbolic cosine function, and ; Based on the adaptive strategy, an adaptive extended state observer is constructed, with the specific expression as follows: ； in, To control input variables, This is the estimated total disturbance. Displacement estimate The first-order time derivative, Speed ​​estimate The first-order time derivative, The actual control gain of the system The per-unit value; Step S3: Construct a pre-compensated global sliding surface based on state variables, and construct a global sliding control law based on Lyapunov stability theory; Step S4: Introduce the total disturbance estimate into the global sliding mode control law, construct the controller, and output the control input variables; Step S5: Construct the objective function, optimize and tune the controller parameters, and obtain the optimal parameter combination; Step S6: Based on the optimal parameter combination, apply the controller constructed in step S4 to the displacement system of the hydraulic anchor drilling rig to achieve closed-loop control of the displacement.

2. The global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO according to claim 1, characterized in that, Step S3 specifically includes: remember To track the signal, let the tracking estimation error be... Construct a pre-compensated sliding mode function The specific expression is: ； in, This is the error scaling factor for the pre-compensation sliding mode function, and , To track estimation error The first-order time derivative; Constructing a fast convergence function The specific expression is: ； in, For runtime, For frequency adjustment parameters; Based on pre-compensated sliding mode function and fast convergence function Construct a pre-compensated global sliding surface The specific expression is: ； in, For pre-compensation sliding mode function The initial value; make , and To meet For odd numbers, based on Lyapunov stability theory, a global sliding mode control law is constructed, the specific expression of which is: ； in, To track the proportional coefficient of the differential term of the estimation error, To track signals The second-order time derivative, For pre-compensated global sliding surface Gain coefficient, For fast convergence function The first-order time derivative, This is the output variable of the global sliding mode control law.

3. The global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO according to claim 2, characterized in that, In step S4, the total disturbance estimate is introduced into the global sliding mode control law to construct the controller, the specific expression of which is: ； in, This is the estimated total disturbance. To control input variables.

4. The global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO according to claim 3, characterized in that, In step S5, the objective function is constructed using the particle swarm optimization algorithm. The specific expression is: ； ； ； ； ； ； ； in, The mean; Standard deviation; To track error indicators; To control energy indicators; For robustness indicators; For sliding mode chattering index; For overshoot indicators; To adjust time indicators; The system outputs the maximum value; This is a reference signal for displacement tracking. This refers to the actual settling time from startup to reaching steady state. For tracking error, and , Output variables for the system; for The first-order time differential.

5. The global sliding mode displacement control method for hydraulic anchor drilling rigs based on PSO and adaptive ESO according to claim 4, characterized in that, The control method ensures that the displacement output of the hydraulic anchor drilling rig displacement system remains stable within a finite time, and the specific expression for the convergence time is as follows: ； in, Lyapunov function initial value, To shorten the convergence time, where are the positive definite coefficients of the Lyapunov function, and .

6. A global sliding mode displacement control system for hydraulic anchor drilling rigs based on PSO and adaptive ESO, employing the method described in any one of claims 1-5, characterized in that, include: The data acquisition module is used to acquire the state variables of the hydraulic anchor drilling rig displacement system; The adaptive extended state observer module, connected to the data acquisition module, is used to construct an adaptive extended state observer based on state variables, estimate the total system disturbance in real time, and output the total disturbance estimate. The global sliding mode control module, connected to the data acquisition module, is used to construct a pre-compensated global sliding surface based on state variables and to construct a global sliding mode control law based on Lyapunov stability theory. The controller construction module is connected to the adaptive extended state observer module and the global sliding mode control module, respectively. It is used to introduce the total disturbance estimate into the global sliding mode control law, construct the controller, and output the control input variable. The parameter optimization module is connected to the adaptive extended state observer module, the global sliding mode control module, and the controller construction module, respectively, and is used to optimize and tune the controller parameters to obtain the optimal parameter combination. The control execution module, connected to the controller construction module, is used to apply the controller to the hydraulic anchor drilling rig displacement system based on the optimal parameter combination, thereby achieving closed-loop control of the displacement.

7. The global sliding mode displacement control system for hydraulic anchor drilling rigs based on PSO and adaptive ESO according to claim 6, characterized in that, The parameter optimization module uses the particle swarm optimization algorithm to construct an objective function with the goal of improving system control accuracy and response speed, and optimizes and tunes the controller parameters.

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