New approach of sliding mode control for nonlinear uncertain pneumatic artificial muscle manipulator enhanced with adaptive fuzzy estimator

Ánh, Hồ Phạm Huy; Kien, Cao Van; Sơn, Nguyễn Ngọc; Nam, Nguyen Thanh

doi:10.1177/1729881418773204

Cited by 13 publications

(7 citation statements)

References 27 publications

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“…Compared with the method of eliminating high-frequency chattering directly by using saturated function [14], we use fuzzy control strategy to modify the robust term coefficient, so as to ensure the rapidity and robustness of the sliding mode control. From (8), the robust term of PI robust sliding mode control is as follows:…”

Section: Improvement Of the Sliding Mode Controlmentioning

confidence: 99%

Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Zhang

et al. 2022

Robotica

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Pneumatic muscle actuator (PMA) similar to biological muscle is a new type of pneumatic actuator. The flexible manipulator based on PMAs was constructed to simulate the actual movement of the human upper arm. Considering the model errors and external disturbances, the fuzzing sliding mode control based on the saturation function was proposed. Compared with other fuzzy control methods, fuzzy control and saturation function are used to adjust the robust terms to improve the tracking accuracy and reduce the high-frequency chattering.

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Section: Improvement Of the Sliding Mode Controlmentioning

confidence: 99%

Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Zhang

et al. 2022

Robotica

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“…Accordingly, the proposed controller (Self-tuning-FSMC) has powerful resistance and can solve the problems of both structured and unstructured uncertainties (Kapoor & Ohri, 2017;Medhaar et al, 2006). In (Anh et al, 2018), an adaptive fuzzy sliding mode controller (AFSMC) to demonstrate the stability of a robotic manipulator system using Lyapunov stability theorem was presented. Similarly, an AFSMC was proposed in (Zhang et al, 2020) to improve the trajectory tracking accuracy of a 3-DOF serial manipulator with parameters uncertainties.…”

Section: Related Workmentioning

confidence: 99%

Modeling and control of a 3-DOF articulated robotic manipulator using self-tuning fuzzy sliding mode controller

2021

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Robotic manipulators are highly coupled multi-input multi-output (MIMO) nonlinear systems with uncertainties and highly time-varying dynamic capabilities. These characteristics make the trajectory control of a robotic manipulator very challenging. This paper presents the modeling and trajectory tracking control of a 3-DOF robotic manipulator using self-tuning fuzzy sliding mode controller (ST-FSMC). The stability of the system was investigated using the Lyapunov direct method. The controller was implemented using MATLAB/Simulink and its performance was evaluated. The simulation results show that the proposed controller removed chattering phenomena from the control effort and reduced the tracking error (average steady-state error) to 0.0036 rad. However, in the case of the conventional controllers, the average steady-state error increased to 0.0413 rad, 0.0044 rad, and 0.0053 rad for the Proportional-integral-derivative (PID) controller, Sliding mode controller (SMC), and Fuzzy sliding mode controller (FSMC), respectively. The conventional controllers (PID, SMC, and FSMC) were designed for the Aderajew Ashagrie

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“…8 As a special nonlinear control method, SMC is widely used in robot control. [9][10][11][12] However, the robustness of SMC exists only in the sliding mode, and the system is still affected by uncertainty and external disturbance in the reaching mode. The chattering phenomenon will increase energy consumption, and it is easy to excite unmodeled high-frequency dynamics that lead to system instability.…”

Section: Introductionmentioning

confidence: 99%

A novel constraint tracking control with sliding mode control for industrial robots

Liu

et al. 2021

International Journal of Advanced Robotic Systems

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As industrial robots are characterized by flexibility, load variation, and unknown interference, it is necessary to develop a control strategy with strong robustness and adaptability, fast convergence rate, and simple structure. Sliding mode control is a special method widely used to handle nonlinear robot control. However, the existing control law for sliding mode control has limitations in the chattering and convergence rate. The sliding mode manifold and reaching law are firstly discussed in this article. In the meanwhile, a proposed control law for sliding mode control combining linear sliding mode manifold and double-power reaching law is developed, which is based on the robot dynamic equation derived by the Udwadia–Kalaba theory. Furthermore, a compared control law for sliding mode control combining linear sliding mode manifold with exponential reaching law is presented to test the proposed control law for sliding mode control. The comparison indicates that the proposed law effectively improves the performance in convergence rate and the chattering of constraint tracking control. Finally, the two control laws for sliding mode control are applied to the Selective Compliance Articulated Robot Arm robot system with modeling error and uncertain external disturbance to demonstrate the merit and validation of the proposed scheme.

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New approach of sliding mode control for nonlinear uncertain pneumatic artificial muscle manipulator enhanced with adaptive fuzzy estimator

Cited by 13 publications

References 27 publications

Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Modeling and control of a 3-DOF articulated robotic manipulator using self-tuning fuzzy sliding mode controller

A novel constraint tracking control with sliding mode control for industrial robots

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