Adaptive Fuzzy Control for a Constrained Robot in the Presence of Input Nonlinearity

Abstract

An adaptive fuzzy finite-time control policy is developed for an uncertain $n$-link robot with input saturation and time-varying output constraints. Compared with previous works, the introduced finite-time stability criterion is used for the tracking control of the robot. Furthermore, cot-type Barrier Lyapunov functions (BLFs) are introduced for guaranteeing output constraints, which can be considered as a substitution of other BLFs. A fuzzy approximation-based adaptive finite-time control scheme is constructed for stabilizing the robotic system. With Lyapunov theory, it has been proved that all the error signals are semi-global practical finite-time stable (SGPFS). At last, the effectiveness of the proposed scheme is verified by simulation results.