A new design of adaptive robust fuzzy controller for nonlinear systems

This paper presents an adaptive robust fuzzy control architecture for a class of nonlinear dynamic systems which are either ill-defined or rather complex. The control objective is to adaptively compensate for the unknown plant nonlinearity, which is represented as a fuzzy rule-base consisting of a collection of if-then rules. The algorithm embedded in the proposed architecture can automatically update fuzzy rules and, consequently, is guaranteed to be globally stable and to drive the tracking errors to a neighborhood of zero. Focused on realization, hardware limitations such as traditional long computation time and excessive memory-space usage are also relaxed by incorporating heuristic concepts, which reveals the flexible feature of this architecture. Simulations are run for the control of a simplified circuit system, and results show that the proposed control architecture is featured in fast convergence