Adaptive Neural Observer-Based Nonsingular Terminal Sliding Mode Controller Design for a Class of Nonlinear Systems
Proceedings - 2019 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019
Neural Networks (NN), Nonlinear System, Observer Design, Terminal Sliding Mode Controller
© 2019 IEEE. Solving the problem of control, stability, and maneuvering of an Air-Cushion Vehicle (ACV), as a nonlinear system, is a key challenge in amphibious vehicles. Nonlinearity, external disturbances, internal uncertainties, and unmodeled dynamics are the main difficulties that an ACV is faced with in the maneuver control. In this paper, a methodology is derived from designing an observer-based controller for an ACV. An adaptive Neural Networks (NN) observer with guaranteed stability is designed for the nonlinear dynamics of an ACV, which is controlled by the nonsingular terminal sliding mode controller. It is assumed that states of the system are unknown, while the system is observable. The main merits of the proposed method are the Lyapunov stability of the closed-loop system, the convergence of the tracking and observer errors to zero, and robustness against uncertainties. Simulation results demonstrate the performance of the proposed method.
Karami, Hamede; Ghasemi, Reza; and Mohammadi, Fazel. (2019). Adaptive Neural Observer-Based Nonsingular Terminal Sliding Mode Controller Design for a Class of Nonlinear Systems. Proceedings - 2019 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019.