Establishment and Experimental Verification of a Nonlinear Position Servo System Model for a Magnetically Coupled Rodless Cylinder

Zhang, Yeming; Li, Kaimin; Cai, Maolin; Feng, Wei; Gong, Sanpeng; Li, Shuping; Lv, Bao-Zhan

doi:10.3390/act11020050

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…The nonlinear characteristics of the pneumatic servo system were the main factors limiting its control accuracy. Zhang et al [14] proposed a new mathematical model of the nonlinear system of the valve control cylinder to improve the control accuracy of the pneumatic servo system. Regarding the perception technology for measuring the status of workface equipment, Wang et al [15] proposed a method for measuring the motion distance of hydraulic supports based on machine vision, and they obtained good measurement results in the experimental stage.…”

Section: Introductionmentioning

confidence: 99%

Research on Positioning Control Strategy for a Hydraulic Support Pushing System Based on Iterative Learning

Hou,

Kou,

et al. 2023

Actuators

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At present, the positioning control of the hydraulic support pushing systems in fully mechanized mining faces uses an electrohydraulic directional valve as the control component, while the current research mainly focuses on servo valves, proportional valves, high−speed on−off valves, and electromagnetic directional valves. At present, the positioning control for electrohydraulic directional valves is only a simple logical control. Therefore, in order to improve the positioning control accuracy of the hydraulic support pushing system, a predictive positioning control strategy based on iterative learning was designed. Firstly, mathematical modeling of the hydraulic support pulling process was carried out, and its state−space equation was established. Secondly, an iterative learning controller with a state observer was designed, in which the iterative learning method was used to predict the control advance in the positioning process, and the state observer was used to estimate the parameters that could not be measured by the system, so as to improve the control accuracy in the broaching process. Then, a SimulationX–Simulink joint simulation model of the position control system of a multi−cylinder pulling hydraulic support was built, and the designed iterative learning controller was compared with the BP neural network controller. Finally, a test platform for the hydraulic support pushing system was built, and the proposed control strategy was experimentally verified. The research results show that the iterative learning control strategy proposed for the electrohydraulic directional valve not only simplifies the design process of the controller but also has higher positioning control accuracy. The single−cylinder positioning control accuracy can be controlled within 10 mm, and the multi−cylinder coordinated positioning control accuracy can be controlled within 15 mm, which meets the accuracy requirements of the site.

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Section: Introductionmentioning

confidence: 99%

Research on Positioning Control Strategy for a Hydraulic Support Pushing System Based on Iterative Learning

Hou,

Kou,

et al. 2023

Actuators

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Enhancing pressure control of low-friction pneumatic actuator with eddy current damper via valve dead-zone compensation

Chen,

Liu,

Wang

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part C:

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This article addresses the high-performance pressure control of a pneumatic actuator that incorporates an air-bearing piston and an eddy current damper (ECD). After optimizing the pneumatic actuator, achieving precise pressure control relies on maintaining an accurate and stable airflow through the control valve. A terminal sliding mode adaptive control method (TSMAC) is proposed, proficiently integrating considerations for dead zone nonlinearities in the proportional valve and the effects of unmodeled disturbances in the pneumatic actuator. Using the opening area of the proportional valve as the input to the pneumatic system greatly simplifies the control process and reduces the workload required for valve parameter calibration. The Lyapunov-based stability analysis demonstrates that excellent asymptotic output tracking can be achieved with low steady-state error simply by knowing the boundaries of the valve opening area. The control effect of the proposed control strategy is compared with an adaptive backstepping sliding mode control method based on a linearly fitted proportional valve model on an established constant pressure control test bench. Experimental results under various loads and operating conditions illustrate the effectiveness of the proposed approach.

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Research on PID Position Control of a Hydraulic Servo System Based on Kalman Genetic Optimization

et al. 2022

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With the wide application of hydraulic servo technology in control systems, the requirement of hydraulic servo position control performance is greater and greater. In order to solve the problems of slow response, poor precision, and weak anti-interference ability in hydraulic servo position controls, a Kalman genetic optimization PID controller is designed. Firstly, aiming at the nonlinear problems such as internal leakage and oil compressibility in the hydraulic servo system, the mathematical model of the hydraulic servo system is established. By analyzing the working characteristics of the servo valve and hydraulic cylinder in the hydraulic servo system, the parameters in the mathematical model are determined. Secondly, a genetic algorithm is used to search the optimal proportional integral differential (PID) controller gain of the hydraulic servo system to realize the accurate control of valve-controlled hydraulic cylinder displacement in the hydraulic servo system. Under the positioning benchmark of step signal and sine wave signal, the PID algorithm and the genetic optimized PID algorithm are compared in the system simulation model established by Simulink. Finally, to solve the amplitude fluctuations caused by the GA optimized PID and reduce the influence of external disturbances, a Kalman filtering algorithm is added to the hydraulic servo system to reduce the amplitude fluctuations and the influence of external disturbances on the system. The simulation results show that the designed Kalman genetic optimization PID controller can be better applied to the position control of the hydraulic servo system. Compared with the traditional PID control algorithm, the PID algorithm optimized by genetic algorithm improves the system’s response speed and control accuracy; the Kalman filter is a good solution for the amplitude fluctuations caused by GA-optimized PID that reduces the influence of external disturbances on the hydraulic servo system.

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Establishment and Experimental Verification of a Nonlinear Position Servo System Model for a Magnetically Coupled Rodless Cylinder

Cited by 4 publications

References 8 publications

Research on Positioning Control Strategy for a Hydraulic Support Pushing System Based on Iterative Learning

Research on Positioning Control Strategy for a Hydraulic Support Pushing System Based on Iterative Learning

Enhancing pressure control of low-friction pneumatic actuator with eddy current damper via valve dead-zone compensation

Research on PID Position Control of a Hydraulic Servo System Based on Kalman Genetic Optimization

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