Adaptive designated-time fuzzy event-triggered tracking of constrained nonlinear systems and its applications in robotic systems

Lifang Qiu; Junsheng Zhao; Lifang Qiu; Junsheng Zhao

doi:10.3934/math.2026645

AIMS Mathematics

2026, Volume 11, Issue 6: 15691-15715. doi: 10.3934/math.2026645

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Research article

Adaptive designated-time fuzzy event-triggered tracking of constrained nonlinear systems and its applications in robotic systems

Lifang Qiu ,
Junsheng Zhao ^,

School of Mathematics and Systems Science, Liaocheng University, Liaocheng, Shandong 252059, China

Received: 26 March 2026 Revised: 21 May 2026 Accepted: 27 May 2026 Published: 04 June 2026
MSC : 93D05, 68T27

This paper develops a designated-time adaptive tracking control strategy for nonlinear systems subject to multiple sources of uncertainty, including output constraints, unmodeled dynamics, and unknown disturbances. By incorporating an enhanced fuzzy logic system for parameter estimation and a bounded command filtering approach, this work proposes a systematic tracking control scheme that effectively avoids the issue of computational complexity explosion. To address the significant uncertainties induced by constraints, an asymmetric barrier Lyapunov function is used for analysis and design under the condition of known control coefficients. Furthermore, a controller constructed based on an event-triggered mechanism ensures uniform boundedness and designated-time convergence of all signals. The feasibility and effectiveness of the proposed control method are validated through a practical application case.
- designated-time stabilization,
- output constraint,
- fuzzy logic system,
- event-triggered mechanism
Citation: Lifang Qiu, Junsheng Zhao. Adaptive designated-time fuzzy event-triggered tracking of constrained nonlinear systems and its applications in robotic systems[J]. AIMS Mathematics, 2026, 11(6): 15691-15715. doi: 10.3934/math.2026645

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Abstract

This paper develops a designated-time adaptive tracking control strategy for nonlinear systems subject to multiple sources of uncertainty, including output constraints, unmodeled dynamics, and unknown disturbances. By incorporating an enhanced fuzzy logic system for parameter estimation and a bounded command filtering approach, this work proposes a systematic tracking control scheme that effectively avoids the issue of computational complexity explosion. To address the significant uncertainties induced by constraints, an asymmetric barrier Lyapunov function is used for analysis and design under the condition of known control coefficients. Furthermore, a controller constructed based on an event-triggered mechanism ensures uniform boundedness and designated-time convergence of all signals. The feasibility and effectiveness of the proposed control method are validated through a practical application case.

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