Dynamic Event-Triggered Adaptive Asymptotic Tracking Control of Uncertain Systems With Unified Prescribed Performance
Kai Zhao, Yuhang Huang, Yongcheng Zhou
Abstract
This paper presents a dynamic event-triggered unified performance adaptive control method for nonparametric strict-feedback nonlinear systems. In contrast to most existing static/dynamic event-driven controllers that only guarantee uniformly ultimately bounded tracking results, here by introducing an external auxiliary variable into the dynamic threshold strategy and using the robust technique with the integral function, not only the communication overhead is reduced and the Zeno phenomenon is precluded, but also the asymptotic zero-error tracking is achieved. The control design and stability analysis become quite complicated and challenging when the performance constraint is taken into account. By constructing a series of functional transformations in conjunction with the core information technique to handle the nonparametric uncertainty, the proposed controller is able to guarantee multiple prescribed performance characteristics by appropriately adjusting the key design parameter, eliminating the need to redesign the controller and reanalyze the stability. Finally, simulation results are conducted to demonstrate the effectiveness of the theoretical discussion.