Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints
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.
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Traditional methods based on Lyapunov-Krasovskii functionals are generally less effective in managing input delays compared to state delays.
“Traditional methods based on Lyapunov-Krasovskii functionals are generally less effective in managing input delays compared to state delays [25][26][27].”
From Fixed-Time Adaptive Control for Nonstrict-Feedback Nonlinear Systems with Input Delay and Unknown Backlash-Like Hysteresis (2025) · cites this paper as [27]
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- Authors
- Li, D.-P., Li, D.-J., Liu, Y.-J., Tong, S., & Chen, C. L. P.
- Affiliations
- Liaoning University of Technology (CN)
- University of Macau (MO)
- Venue
- IEEE Transactions on Cybernetics
- Published
- 2017-10
- Volume
- 47
- Issue
- 10
- Pages
- 3100-3109
- ISSN
- 2168-2267 (ISSN-L)
- 2168-2275
- OpenAlex
- W2625591652
- Cited by
- 148
- References
- 72
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 11 · 2023: 8 · 2022: 12 · 2021: 25 · 2020: 21 · 2019: 26 · 2018: 26 · 2017: 6
- FWCI
- 13.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Cybernetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (61603164, 61473139, 61622303)
- Project for Distinguished Professor of Liaoning Province
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Physical Sciences › Computer Science › Computer Networks and Communications › Neural Networks Stability and Synchronization
- Keywords
- tracking control, MIMO nonlinear systems, unknown time-varying delays, full-state constraints, adaptive neural network control, Lyapunov-Krasovskii functional, separation processes, barrier Lyapunov function, signal function, closed-loop boundedness
- MeSH terms
- Computer Simulation, Signal Processing, Computer-Assisted, Time Factors, Neural Networks, Computer, Nonlinear Dynamics
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