Event-Triggered Adaptive Tracking Control for Random Systems With Coexisting Parametric Uncertainties and Severe Nonlinearities
Huaguang Zhang, Ruipeng Xi, Yingchun Wang, Shaoxin Sun, Jiayue Sun
Abstract
Comparing with traditional stochastic differential equations involving white noise, random differential equations (RDEs) with colored noise are claimed to have more practical meaning. This article considers the event-triggered adaptive tracking control for RDE systems with coexisting parametric uncertainties and severe nonlinearities. Combining a tracking error-based dynamic gain with a relative threshold event triggered control mechanism, the tracking control problem for the random systems is solved without Zeno behavior. The tracking error can be rendered small enough by tuning design parameters. First, a series of adaptive control laws are designed by using backstepping technique. Then, two special cases are considered and the main results are extended to MIMO systems. Finally, a simulation example confirms the validity of the results. To the best of the authors’ knowledge, this article serves as the first attempt of event-based control for RDE systems.