Event-Triggered Adaptive Tracking Control for Random Systems With Coexisting Parametric Uncertainties and Severe Nonlinearities

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.

Automated summary

This article explores event-triggered adaptive tracking control for RDE systems with parametric uncertainties and severe nonlinearities, solving the tracking control problem without Zeno behavior by combining dynamic gain and event-triggered control mechanism. Tuning design parameters can reduce tracking errors, with adaptive control laws designed using backstepping technique and results extended to MIMO systems. Simulation example validates the results, marking the first attempt of event-based control for RDE systems.