Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output ConstraintsOACSTPCDEI
Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints
The problem of prescribed performance tracking control for unknown time-delay nonlinear systems subject to out-put constraints is dealt with in this paper.In contrast with related works,only the most fundamental requirements,i.e.,bounded-ness and the local Lipschitz condition,are assumed for the allow-able time delays.Moreover,we focus on the case where the refer-ence is unknown beforehand,which renders the standard pre-scribed performance control designs under output constraints infeasible.To conquer these challenges,a novel robust prescribed performance control approach is put forward in this paper.Herein,a reverse tuning function is skillfully constructed and automatically generates a performance envelop for the tracking error.In addition,a unified performance analysis framework based on proof by contradiction and the barrier function is estab-lished to reveal the inherent robustness of the control system against the time delays.It turns out that the system output tracks the reference with a preassigned settling time and good accuracy,without constraint violations.A comparative simulation on a two-stage chemical reactor is carried out to illustrate the above theo-retical findings.
Jin-Xi Zhang;Kai-Di Xu;Qing-Guo Wang
State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University,Shenyang 110819,ChinaInstitute of Artificial Intelligence and Future Networks,Beijing Normal University,Zhuhai 519087||Guangdong Key Laboratory of Artificial Intelligence and Multi-Modal Data Processing,Beijing Normal University-Hong Kong Baptist University United Inter-national College,Zhuhai 519087,China
Nonlinear systemsoutput constraintsprescribed performancereference trackingtime delays
《自动化学报（英文版）》 2024 (007)
1557-1565 / 9
This work was supported in part by the National Natural Science Foundation of China(62103093),the National Key Research and Development Program of China(2022YFB3305905),the Xingliao Talent Program of Liaoning Province of China(XLYC2203130),the Fundamental Research Funds for the Central Universities of China(N2108003),the Natural Science Foundation of Liaoning Province(2023-MS-087),the BNU Talent Seed Fund,UIC Start-Up Fund(R72021115),the Guangdong Key Laboratory of AI and MM Data Processing(2020KSYS007),the Guangdong Provincial Key Laboratory IRADS for Data Science(2022B1212010006),and the Guang-dong Higher Education Upgrading Plan 2021-2025 of"Rushing to the Top,Making Up Shortcomings and Strengthening Special Features"with UIC Research,China(R0400001-22,R0400025-21).Editor Qing-Long Han.
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