Switching Threshold‐based Event‐triggered Adaptive Asymptotic Tracking Control for Stochastic Nonlinear Systems with Full‐state Constraints

In this article, the problem of event-triggered adaptive asymptotic tracking control (ATC) for stochastic nonlinear systems with unknown control directions (UCDs) and full state constraints is concerned. It must be said that the controller design and system analysis is more complex and difficult since the existence of stochastic disturbances, UCDs and full state constraints simultaneously. By introducing the lower bound of the UCDs into the barrier Lyapunov functions, an event-triggered adaptive MTN ATC scheme is proposed based on the boundary estimation method and a new event-triggered control (ETC) strategy, which can achieve satisfactory asymptotic tracking performance and control performance of the system, while reduce the occupation of network resources. The simulation results not only verify the effectiveness of the proposed control scheme, but also present different tracking performances between three ETC strategies for comparison, further confirming the superiority of the proposed ETC strategy in achieving asymptotic tracking performance.

International Journal of Robust and Nonlinear Control