Event-Triggered Fixed-Time Practical Tracking Control for Flexible-Joint Robot
Yingkang Xie, Qian Ma, Jason Gu, Guopeng Zhou
Abstract
This article studies the adaptive fuzzy event-triggered fixed-time practical tracking control problem for flexible-joint robot system. Since the nonlinearities of the system are difficult to obtain, fuzzy logic systems are utilized. Second-order command filters are used to avoid the “explosion of complexity” problem. Moreover, a novel compensation system is proposed. The new error compensation system cannot only compensate for the error of the filter band, but also make the error converge in fixed time. By using backstepping technique, the virtual control laws and the adaptive law are designed. Notice that compared to the reporting achievements, our proposed virtual control laws are second-order derivable by using the novel switch function, which avoids “singularity hindrance” problem. To reduce communication pressure, the event-triggered controller is designed and Zeno behavior is avoided. Our proposed control strategy ensures that the tracking error can be arbitrarily small in fixed time and all variables of the closed-loop system remain bounded. Finally, simulation results are given to show the effectiveness of our control strategy.