Adaptive Fuzzy Control for Flexible Robotic Manipulator with a Fixed Sampled Period

Abstract

In this paper, a backstepping sampled data control method is developed for a flexible robotic manipulator whose internal dynamic is completely unknown. To address the internal uncertainties, the fuzzy logical system (FLS) is considered. Moreover, considering the limited network bandwidth, the designed controller and adaptive laws only contain the sampled data with a fixed sampled period. By invoking the Lyapunov stability theory, all signals of the flexible robotic manipulator are semi-global uniformly ultimately bounded (SGUUB). Ultimately, an application to a flexible robotic manipulator is given to verify the validity of the sampled data controller.