Switching Adaptive Control with Applications on Robot Manipulators - Shihao Wang; Shiqi Zheng; Yushu Deng; Zhouxiang Jiang; Bao Song; Xiaoqi Tang (Entropy, 2022)
This paper concentrates on the study of logic-based switching adaptive control. Two different cases will be considered. In the first case, the finite time stabilization problem for a class of nonlinear system is studied. Based on the recently developed adding a barrier power integrator technique, a new logic-based switching adaptive control method is proposed. In contrast with the existing results, finite time stability can be achieved when the considered systems contain both fully unknown nonlinearties and unknown control direction. Moreover, the proposed controller has a very simple structure and no approximation methods, e.g., neural networks/fuzzy logic, are needed. In the second case, the sampled-data control for a class of nonlinear system is investigated. New sampled-data logic-based switching mechanism is proposed. Compared with previous works, the considered nonlinear system has an uncertain linear growth rate. The control parameters and the sampling time can be adjusted adaptively to render the exponential stability of the closed loop system. Applications in robot manipulators are conducted to verify the proposed results.