Adaptive fuzzy control design for nonlinear systems with actuation and state constraints: An approach with no feasibility condition

Abstract

In this article, an adaptive fuzzy tracking control scheme is developed for a class of pure-feedback uncertain nonlinear systems in the presence of time-varying full-state constraints (TFSCs), actuators’ nonlinearities and external disturbances. Fuzzy logic systems (FLSs) are employed as universal approximators to online estimate unknown nonlinear functions A barrier Lyapunov function (BLF) is used to deal with the state constraint problem. In contrast to numerous adjacent studies, this research diligently tackles the open problem relating to the virtual control laws (VCLs) feasibility in the BLF-based backstepping control design. The resolution to this problem involves formulating VCLs with predefined bounds. The utilization of disturbance observers within a backstepping framework allows for effective compensation of estimation errors arising from the implementation of a predefined bounded VCL. This approach also helps prevent the occurrence of the ”complexity explosion”, making it a practical solution. The control strategy being proposed guarantees that the output tracking error will effectively approach a small region near the origin. Additionally, all signals of the closed-loop system will remain uniformly ultimately bounded (UUB), and there will be adherence to all state-constraints, ensuring no violations occur. Ultimately, an illustrative simulation example is provided to demonstrate the efficacy of the theoretical findings.