Hybrid Event-triggered Control of Nonlinear System with Full State Constraints and Disturbance

Abstract

This article focuses on the problem of adaptive tracking control for a specific type of nonlinear system that is subject to full-state constraints via a hybrid event-triggered control (HETC) strategy. With the auxiliary system, we proposed a 'log' function to deal with the full-state constraint. Additionally, a disturbance observer (DO) is constructed to handle the unmeasurable external disturbance. Then, by employing radial basis function neural networks (RBFNNs) and a first-order differentiator, an opportune backstepping design procedure is given to avoid the problem of "explosion of complexity". The HETC strategy, including the fixed and relative threshold, is presented to provide more flexibility in balancing the system performances and network burdens. Finally, to demonstrate the effectiveness of the aforementioned control scheme, a simulation example is presented to validate its effectiveness.