Incremental networked predictive control of multi‐agent systems with plant‐model mismatch and random communication constraints
Abstract In this paper, we discuss the cooperative output tracking problem for networked multi‐agent systems (NMASs) with plant‐model mismatch as well as random communication constraints in the forward and feedback channels of each agent. In order to compensate actively for random communication cons...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Wiley
2022
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/49669ca96da0488b8c877c123619f1e9 |
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| Sumario: | Abstract In this paper, we discuss the cooperative output tracking problem for networked multi‐agent systems (NMASs) with plant‐model mismatch as well as random communication constraints in the forward and feedback channels of each agent. In order to compensate actively for random communication constraints, that is, network‐induced delays and packet dropouts, an incremental networked predictive control scheme based on a state observer is proposed, which consists of a data buffer, an incremental networked predictor, and a network delay compensator. For both the plant‐model mismatch case and the plant‐model match case, the stability conditions of resulting closed‐loop NMASs are derived, respectively. Using the proposed method, the simulation results for three DC motor systems are presented to indicate that desired tracking performance can be achieved. |
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