BLF-based Adaptive Fuzzy DSC for a class of Uncertain Nonlinear Systems with Full State Constraints and Input Saturation using Disturbance Observer

This paper focus on a novel research for dynamic surface adaptive fuzzy tracking control of uncertain strict-feedback nonlinear systems subject to full state constraints, actuator' saturation, and unmatched external disturbances. The adaptive fuzzy models are employed to online approximate some uncertain smooth functions. Correspondingly, the dynamic surface control (DSC) concept is introduced to effectively cope with the well-known issue of "explosion of complexity" intrinsically related to backstepping methodology. The problem of state constraints is solved by using a suitable barrier Lyapunov function (BLF). To practically deal with unmatched disturbances, disturbance observers are designed. The proposed controller ensures the convergence of the output tracking error to an arbitrarily tiny neighborhood of the origin, boundedness of all closed-loop signals and no-violation of the predefined state constraints. Finally, an application to a practical system verifies the validity of our proposed control method.