Event‐Triggered Adaptive Asymptotic Tracking Control for Stochastic Non‐Linear Systems With Unknown Hysteresis: A New Switching Threshold Approach
Abstract
ABSTRACT This paper proposes a novel event‐triggered adaptive asymptotic tracking control (ATC) method for stochastic non‐linear systems with unknown hysteresis. Firstly, in order to reduce the depletion of network resources while optimizing the asymptotic tracking performance of the system, a switching threshold mechanism (STM)‐based event‐triggered control (ETC) strategy is adopted. Secondly, a first‐order filter is utilized to address the problem of the contradiction between event‐triggered mechanism (ETM) output and rate‐dependent hysteresis actuator input. By incorporating an enhanced backstepping technique and a bounded estimation method, it is rigorously demonstrate that the system achieves zero tracking error, effectively compensates for unknown hysteresis, and ensures that all closed‐loop signals remain bounded in probability. Meanwhile, the Zeno phenomenon is excluded. Finally, the effectiveness and superiority of the proposed control scheme are verified by the simulation results.
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