This paper is concerned with the problem of adaptive neural network (NN) tracking control for a class of uncertain switched nonlinear systems with time delays. Compared with the existing results, a new common Lyapunov function with switched adaptive parameters is constructed. The unknown functions with time-delay state are compensated by using appropriate Lyapunov–Krasovskii functionals in the design. To guarantee transient performance of switched systems with time delays, the prescribed performance bound (PPB) method is utilized. Based on convex combination technique, a novel adaptive NN tracking control method under state-dependent switching law is proposed. It is shown that under the proposed control and switching laws, all the signals of the closed-loop system are bounded and the tracking error is preserved within PPB. Finally, the simulation example is given to demonstrate the effectiveness of the proposed control scheme.
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Adaptive Neural Network Control for Uncertain Switched Nonlinear Systems With Time Delays
Semantic Scholar · Computer Science · 2018
Abstract
This paper is concerned with the problem of adaptive neural network (NN) tracking control for a class of uncertain switched nonlinear systems with time delays. Compared with the existing results, a new common Lyapunov function with switched adaptive parameters is constructed. The unknown functions with time-delay state are compensated by using appropriate Lyapunov–Krasovskii functionals in the design. To guarantee transient performance of switched systems with time delays, the prescribed performance bound (PPB) method is utilized. Based on convex combination technique, a novel adaptive NN tracking control method under state-dependent switching law is proposed. It is shown that under the proposed control and switching laws, all the signals of the closed-loop system are bounded and the tracking error is preserved within PPB. Finally, the simulation example is given to demonstrate the effectiveness of the proposed control scheme.