Robust L2 Disturbance Attenuation for Quasi-One-Sided Lipschitz Nonlinear Systems via Sliding Mode Control

Author(s):  
Wajdi Saad ◽  
Anis Sellami ◽  
Germain Garcia
2019 ◽  
Vol 26 (7-8) ◽  
pp. 399-412
Author(s):  
Wajdi Saad ◽  
Anis Sellami ◽  
Germain Garcia

In this paper, the problem of adaptive sliding mode control for varied one-sided Lipschitz nonlinear systems with uncertainties is investigated. In contrast to existing sliding mode control design methods, the considered models, in the current study, are affected by nonlinear control inputs, one-sided Lipschitz nonlinearities, unknown disturbances and parameter uncertainties. At first, to design the sliding surface, a specific switching function is defined. The corresponding nonlinear equivalent control is extracted and the resulting sliding mode dynamic is given. Novel synthesis conditions of asymptotic stability are derived in terms of linear matrix inequalities. Thereafter, to ensure the reachability of system states and the occurrence of the sliding mode, the sliding mode controller is designed. Any knowledge of the upper bound on the perturbation is not required and an adaptation law is proposed. At last, two illustrative examples are introduced.


Author(s):  
Xizheng Zhang ◽  
Yaonan Wang ◽  
Xiaofang Yuan

This paper presents the fuzzy design of sliding mode control (SMC) for nonlinear systems with state delay, which can be represented by a Takagi-Sugeno (TS) model with uncertainties. There exist the parameter uncertainties in both the state and input matrices, as well as the unmatched external disturbance. The key feature of this work is the integration of SMC method with H∞ technique such that the robust asymptotically stability with a prescribed disturbance attenuation level γ can be achieved. A sufficient condition for the existence of the desired SMC is obtained by solving a set of linear matrix inequalities (LMIs). The reachability of the specified switching surface is proven. Simulation results show the validity of the proposed method.


2021 ◽  
pp. 002029402110211
Author(s):  
Tao Chen ◽  
Damin Cao ◽  
Jiaxin Yuan ◽  
Hui Yang

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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