Observer‐based adaptive neural output‐feedback event‐triggered control for discrete‐time nonlinear systems using variable substitution

In this paper, an event‐triggered adaptive neural output feedback control scheme is developed for a class of uncertain discrete‐time strict‐feedback nonlinear systems subject to immeasurable system states and network resource limitation. An i‐step ahead predictor is synthesized to obtain the future...

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Vydané v:International journal of robust and nonlinear control Ročník 31; číslo 12; s. 5541 - 5562
Hlavní autori: Wang, Min, Huang, Longwang, Zhao, Zhijia, Yang, Chenguang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Bognor Regis Wiley Subscription Services, Inc 01.08.2021
Predmet:
Adaptive control
adaptive neural control
Controllers
discrete‐time nonlinear systems
Event triggered control
Feedback control
mismatched nonlinear uncertainties
neural observer
Nonlinear systems
Output feedback
Robot arms
Stability analysis
State estimation
Substitutes
System dynamics
ISSN:1049-8923, 1099-1239
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Shrnutí:In this paper, an event‐triggered adaptive neural output feedback control scheme is developed for a class of uncertain discrete‐time strict‐feedback nonlinear systems subject to immeasurable system states and network resource limitation. An i‐step ahead predictor is synthesized to obtain the future signal of the reference orbit. By combining the neural observer and the variable substitution technology, an event‐triggered adaptive neural control scheme is developed, thereby estimating the immeasurable system states and avoiding the n‐step delays of the existing controller. To promote the transient system performance, an improved triggering condition is designed to increase the number of triggering events in the transient process. The stability analysis of the closed‐loop system is divided into two parts to deal with the challenge from the simultaneous presence of state estimations, unknown system dynamics, and aperiodical controller weight updating laws. The proposed scheme achieves the state estimation, guarantees the output tracking performance with the improved transient control performance, and reduces the communication resource. Simulation studies on a numerical example and a networked robot manipulator are, respectively, implemented to show the validity of the proposed scheme.
Bibliografia:ObjectType-Article-1
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ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.5530