SLIDING MODE CONTROL OF DISCRETE NONLINEAR SYSTEMS IN THE PRESENCE OF UNKNOWN PERTURBATIONS

2000 ◽  
Author(s):  
P. L. CORRIEU ◽  
W. PERRUQUETTI ◽  
J. P. RICHARD
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Mode Control ◽  
Discrete Nonlinear Systems

Sliding Mode-Like Fuzzy Logic Control With Adaptive Boundary Layer for Multiple-Variable Discrete Nonlinear Systems

2016 ◽  
Vol 25 (2) ◽  
pp. 209-220 ◽  
Author(s):  
Xiaoyu Zhang
Keyword(s):  
Boundary Layer ◽  
Fuzzy Logic ◽  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fuzzy Logic Control ◽  
Sliding Mode ◽  
Mode Control ◽  
Logic Control ◽  
Chattering Free ◽  
Discrete Nonlinear Systems

AbstractMore serious chattering emerges in discrete systems of sliding mode control. The paper presents a sliding mode-like fuzzy logic control design, which eliminates the chattering, for a class of discrete nonlinear systems with multiple variables. First, the boundary layer is self-tuned on-line, and then, the chattering free is obtained. Consequently, the fuzzy logic control (FLC) is designed to approximate the sliding mode control (SMC) with boundary layer self-tuning. Finally, the performance of the robustness, chattering free, and adaption are verified by the simulation results.

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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