NN approach to state-feedback control of high-order non-linear time-delay systems with time-varying control coefficient

Abstract

This paper considers the adaptive state-feedback control problem for a class of high-order non-linear systems with unknown control coefficient and time delays. By applying the neural network approximation method and the Nussbaum function approach, the restrictions on non-linear functions and the conditions on the time-varying control coefficient are largely relaxed. In addition, an adaptive neural network state-feedback controller with only one adaptive parameter is successfully constructed by introducing proper Lyapunov–Krasovskii functionals and using the backstepping technique. The proposed scheme guarantees the closed-loop system to be semi-globally uniformly ultimately bounded. Finally, a simulation example demonstrates the effectiveness of the controller.

Prescribed-time state-feedback stabilization of nonlinear systems with unmatched nonlinear terms

“…Tremendous strides have been made on the controller design of nonlinear systems with the rapid development of nonlinear control theory and tools (Chen et al, 2023a(Chen et al, , 2023b(Chen et al, , 2023cKanellakopoulos et al, 1991;Khalil, 2002;Lin and Qian, 2000;Min and Duan, 2018;Qian, 2005;Qian and Lin, 2001;Zhao and Lin, 2021). In the study of the stability of nonlinear systems, asymptotic stability describes the convergence of system state in infinite time.…”