This paper presents an adaptive robust fuzzy control architecture for robot manipulators. The control objective is to adaptively compensate for the unknown nonlinearity of robot manipulators 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 it is guaranteed to be globally stable and to drive the tracking errors to a neighborhood of zero. Focusing 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. The present work is applied to the control of a five degree-of-freedom (DOF) articulated robot manipulator. Experiment results show that the proposed control architecture features fast convergence.
展开▼
