scholarly journals Adaptive super‐twisting algorithm‐based fractional‐order sliding mode control of redundantly actuated cable driving parallel robot with uncertainty and disturbance estimation

2021 ◽  
Author(s):  
Chen Zhengsheng ◽  
Wang Xuesong ◽  
Cheng Yuhu
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Parallel Robot ◽  
Disturbance Estimation ◽  
Mode Control ◽  
Redundantly Actuated ◽  
Twisting Algorithm ◽  
Uncertainty And Disturbance Estimation

Adaptive finite-time disturbance observer-based recursive fractional-order sliding mode control of redundantly actuated cable driving parallel robots under disturbances and input saturation

2021 ◽  
pp. 107754632110514
Author(s):  
Zhengsheng Chen ◽  
Xuesong Wang ◽  
Yuhu Cheng
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Finite Time ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
Estimation Error ◽  
Input Saturation ◽  
Parallel Robots ◽  
Mode Control ◽  
Redundantly Actuated

This paper proposed a novel finite-time disturbance observer-based recursive fractional-order sliding mode control (FTRFOSMC) algorithm under disturbances and input saturation for redundantly actuated cable driving parallel robots (RCDPRs). A recursive fractional-order sliding mode surface composed of the fractional-order non-singular fast terminal sliding mode function and an integral term is constructed, and the fast response convergence and high precision tracking performance can be obtained for the recursive characteristics of the proposed sliding mode surface; meanwhile, an auxiliary system is designed to overcome the adverse effects of the input saturation. Then, to compensate the model uncertainty and external disturbances, an adaptive finite-time disturbance observer is developed, and the estimation error can be stabilized in finite-time for unknown bound of the disturbance and its derivative. The stability of the proposed controller was investigated by the Lyapunov stability theory. Finally, numerical simulations with the software of the MATLAB/Simuink are conducted to verify the effectiveness of the proposed controller.

Sliding Mode Variable Structure Control of a Redundantly Actuated Parallel Robot

2009 ◽  
Vol 626-627 ◽  
pp. 465-470 ◽  
Author(s):  
Y. Li ◽  
Yong Wang
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Variable Structure ◽  
Parallel Robot ◽  
Fast Response ◽  
Mode Control ◽  
Redundantly Actuated ◽  
Sliding Mode Variable Structure ◽  
The Stability ◽  
Object Of Study

Redundant actuation has good performance in eliminating singularities and optimizing force distribution, a 2-DOF redundantly actuated parallel robot is taken as the object of study. The dynamic model of the parallel robot is derived. Because the parallel robot is an uncertain nonlinear system, the sliding mode variable structure controller is designed considering its fast response and robustness. Then the stability of the proposed controller is analyzed. The saturation function is used instead of the sign function to eliminate the chattering of the sliding mode control. The simulation results show that the torque of each servo motor changes smoothly when using the quasi-sliding mode control. So the damage of the servo motors and robot arms is decreased. The results of the trajectory tracking demonstrate the effectiveness of the quasi-sliding mode control.

A diffusive representation approach toward H∞ sliding mode control design for fractional-order Markovian jump systems

2020 ◽  
pp. 095965182097525
Author(s):  
Majid Parvizian ◽  
Khosro Khandani
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Markovian Jump Systems ◽  
Markovian Jump ◽  
Suggested Approach ◽  
Stabilizing Controller ◽  
Mode Control ◽  
Jump Systems ◽  
Diffusive Representation

This article proposes a new [Formula: see text] sliding mode control strategy for stabilizing controller design for fractional-order Markovian jump systems. The suggested approach is based on the diffusive representation of fractional-order Markovian jump systems which transforms the fractional-order system into an integer-order one. Using a new Lyapunov–Krasovskii functional, the problem of [Formula: see text] sliding mode control of uncertain fractional-order Markovian jump systems with exogenous noise is investigated. We propose a sliding surface and prove its reachability. Moreover, the linear matrix inequality conditions for stochastic stability of the resultant sliding motion with a given [Formula: see text] disturbance attenuation level are derived. Eventually, the theoretical results are verified through a simulation example.

scholarly journals Observer-based adaptive neural network backstepping sliding mode control for switched fractional order uncertain nonlinear systems with unmeasured states

2021 ◽  
pp. 002029402110211
Author(s):  
Tao Chen ◽  
Damin Cao ◽  
Jiaxin Yuan ◽  
Hui Yang
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Neural Network ◽  
Dynamic Surface ◽  
Mode Control ◽  
The Stability

This paper proposes an observer-based adaptive neural network backstepping sliding mode controller to ensure the stability of switched fractional order strict-feedback nonlinear systems in the presence of arbitrary switchings and unmeasured states. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. An observer is used for states estimation of the fractional order systems. The sliding mode control technology is introduced to enhance robustness. The unknown nonlinear functions and uncertain disturbances are approximated by the radial basis function neural networks (RBFNNs). The stability of system is ensured by the constructed Lyapunov functions. The fractional adaptive laws are proposed to update uncertain parameters. The proposed controller can ensure convergence of the tracking error and all the states remain bounded in the closed-loop systems. Lastly, the feasibility of the proposed control method is proved by giving two examples.

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