Switching threshold-based event-triggered adaptive tracking control for stochastic nonlinear systems

This paper proposes a novel adaptive tracking control approach for stochastic nonlinear systems with limited resources. To optimize system tracking performance while minimizing the consumption of network resources, an event-triggered control (ETC) strategy based on a switching threshold mechanism (STM) is employed. The paper rigorously demonstrates that the system output can track the desired reference signal. Additionally, the controller is designed to avoid the Zeno phenomenon. Finally, the proposed control method’s effectiveness and superiority are validated through two simulation examples.