Robust adaptive formation control for nonlinear multi-agent systems with range constraints
This paper studies the adaptive distributed formation control design for pure feedback nonlinear multi-agent systems with state time-delay. Neural networks (NNs) are adopted to approximate the unknown nonlinear functions, then Lyapunov–Krasovskii functional and Nussbaum-type function are introduced...
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Veröffentlicht in: | Nonlinear dynamics 2024-02, Vol.112 (3), p.1917-1929 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper studies the adaptive distributed formation control design for pure feedback nonlinear multi-agent systems with state time-delay. Neural networks (NNs) are adopted to approximate the unknown nonlinear functions, then Lyapunov–Krasovskii functional and Nussbaum-type function are introduced to solve the state time-delay and unknown control direction problems, respectively. When considering the limitations of communication and collision, a nonlinear error transformation method is developed to achieve the collision avoidance and connectivity maintenance. Combining adaptive backstepping control and dynamic surface control technique, a robust adaptive NN predetermined time formation tracking control method is developed, which demonstrates that all signals of the closed-loop system are semi- globally uniformly ultimately bounded, and formation tracking error converges to a small neighborhood of origin. Finally, the simulation results are provided to illustrate the effectiveness and feasibility of the developed control method and theory. |
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ISSN: | 0924-090X 1573-269X |
DOI: | 10.1007/s11071-023-09118-x |