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Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints
Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C. L. Philip
2017-10
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
Volume47Issue:10Pages:3100-3109
Abstract

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

KeywordAdaptive Control Barrier Lyapunov Functions (Blfs) Neural Networks (Nns) Nonlinear Multiple Input Multiple Output (Mimo) Time-delay Systems
DOI10.1109/TCYB.2017.2707178
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000409311800012
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
The Source to ArticleWOS
Scopus ID2-s2.0-85020721101
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Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Li, Da-Peng,Li, Dong-Juan,Liu, Yan-Jun,et al. Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints[J]. IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47(10), 3100-3109.
APA Li, Da-Peng., Li, Dong-Juan., Liu, Yan-Jun., Tong, Shaocheng., & Chen, C. L. Philip (2017). Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints. IEEE TRANSACTIONS ON CYBERNETICS, 47(10), 3100-3109.
MLA Li, Da-Peng,et al."Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints".IEEE TRANSACTIONS ON CYBERNETICS 47.10(2017):3100-3109.
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