Adaptive Command Filtered Control for a Class of Random Nonlinear Systems Under Model-Based Event-Triggered Control Design
Ruipeng Xi, Huaguang Zhang, Hailong Huang, Yushuai Li
Abstract
Random nonlinear systems (RNSs) are a class of nondeterministic systems that are distinguished from the intensively studied stochastic nonlinear systems (SNSs). The research on RNSs is becoming more and more popular thanks to its practical significance. To economize communication resources and alleviate network burden, a model-based event-triggered control (MBETC) scheme is applied to a family of RNSs in a strict-feedback fashion. With the help of the adaptive command filtering design technique, all signals of the closed-loop system are rendered ultimately bounded in the mean sense, and the notorious Zeno behavior is circumvented to appear. A simulation example is taken to manifest the validity of the main results.