Quantized-Feedback-Based Adaptive Event-Triggered Control of a Class of Uncertain Nonlinear Systems

Yun Ho Choi,Sung Jin Yoo

doi:10.3390/math8091603

Abstract

A quantized-feedback-based adaptive event-triggered tracking problem is investigated for strict-feedback nonlinear systems with unknown nonlinearities and external disturbances. All state variables are quantized through a uniform quantizer and the quantized states are only measurable for the control design. An approximation-based adaptive event-triggered control strategy using quantized states is presented. Compared with the existing recursive quantized feedback control results, the primary contributions of the proposed strategy are (1) to derive a quantized-states-based function approximation mechanism for compensating for unknown and unmatched nonlinearities and (2) to design a quantized-states-based event triggering law for the intermittent update of the control signal. A Lyapunov-based stability analysis is provided to conclude that closed-loop signals are uniformly ultimately bounded and there exists a minimum inter-event time for excluding Zeno behavior. In simulation results, it is shown that the proposed quantized-feedback-based event-triggered control law can be implemented with less than 10% of the total sample data of the existing quantized-feedback continuous control law.

Highlights

As networked control systems including digital communication channels have been successfully utilized in various industrial applications, significant research efforts have been devoted to control designs using input and state quantization [1,2,3]
We show that the proposed event-triggered control scheme was designed in the presence of unknown nonlinearities, its tracking performance was similar to the performance of the previous continuous controller [14] designed in the presence of known nonlinear functions
A quantized-feedback-based adaptive event-triggered tracking strategy has been provided for state-quantized nonlinear systems in strict-feedback form with unknown nonlinearities

Summary

Introduction

As networked control systems including digital communication channels have been successfully utilized in various industrial applications, significant research efforts have been devoted to control designs using input and state quantization [1,2,3]. Recursive control techniques have attracted much attention as effective ways for dealing with the unmatched nonlinearities of lower-triangular nonlinear systems [4,5,6]. In order to overcome this restriction, an adaptive quantized feedback control design methodology adopting the command filtered backstepping technique for lower-triangular nonlinear systems was recently presented in [14]. Despite this progress, two aspects still need to be addressed to realize further improvement in the quantized feedback control design [14]

Objectives

Results

Conclusion