Event-Triggered Adaptive Prescribed Performance Control for a Class of Uncertain Nonlinear Systems

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6 Citations (Scopus)

Abstract

In this work, we present a new approach to design event-triggered adaptive control for a class of uncertain nonlinear systems with guaranteed performance. A prescribed performance function, which is characterized with the convergence rate, maximum overshoot, and steady error, is utilized to convert the original tracking error into a new error variable, resulting in a transformed error dynamic model. By designing event-triggered control for the transformed error dynamic model, the corresponding control scheme is able to ensure prescribed performance and reduce communication burden simultaneously. Simulation verification also confirms the effectiveness of the proposed approach.
Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1246-1251
Number of pages6
ISBN (Electronic)9781538613955
DOIs
Publication statusPublished - 2 Jul 2018
Externally publishedYes

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Funding

This work was partially supported by the National Natural Science Foundation of China under Grant 61860206008 and 61773081; Fundamental Research Funds for the Central University under Grant 2018CDYJSY0055; the Technology Transformation Program of Chongqing Higher Education University under Grant KJZH17102.

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