Prescribed performance bipartite containment control for multiagent systems with input delay and saturation under fixed‐time framework.
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| Title: | Prescribed performance bipartite containment control for multiagent systems with input delay and saturation under fixed‐time framework. |
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| Authors: | Jiao, Jianmin1,2 (AUTHOR), Li, Junmin1 (AUTHOR) jmli@mail.xidian.edu.cn, Chen, Jiaxi1 (AUTHOR), Zhang, Rui2 (AUTHOR) |
| Source: | Asian Journal of Control. Mar2026, Vol. 28 Issue 2, p922-940. 19p. |
| Subjects: | Multiagent systems, Backstepping control method, Artificial neural networks, Time delay systems |
| Abstract: | This paper investigates the fixed‐time (FT) bipartite containment control (BCC) problem for nonlinear multiagent systems (MASs) with input delay and saturation. A modified FT command filter is proposed to circumvent the computational complexity inherent in the traditional backstepping method. Simultaneously, an ameliorative FT delay compensation mechanism is devised to reduce the negative influence of input delay. Additionally, prescribed performance control (PPC) technology is integrated to enforce performance constraints on the compensated errors. Subsequently, a distributed prescribed performance FT BCC scheme is developed using FT control method, backstepping recursion algorithm, and neural network approximation technology. Finally, numerical simulations of a networked ship fleet are conducted to validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | This paper investigates the fixed‐time (FT) bipartite containment control (BCC) problem for nonlinear multiagent systems (MASs) with input delay and saturation. A modified FT command filter is proposed to circumvent the computational complexity inherent in the traditional backstepping method. Simultaneously, an ameliorative FT delay compensation mechanism is devised to reduce the negative influence of input delay. Additionally, prescribed performance control (PPC) technology is integrated to enforce performance constraints on the compensated errors. Subsequently, a distributed prescribed performance FT BCC scheme is developed using FT control method, backstepping recursion algorithm, and neural network approximation technology. Finally, numerical simulations of a networked ship fleet are conducted to validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15618625 |
| DOI: | 10.1002/asjc.3705 |
