Multiple dynamic targets enclosing control for a class of nonlinear uncertain multiagent systems (Q6571186)
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scientific article; zbMATH DE number 7880049
| Language | Label | Description | Also known as |
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| English | Multiple dynamic targets enclosing control for a class of nonlinear uncertain multiagent systems |
scientific article; zbMATH DE number 7880049 |
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Multiple dynamic targets enclosing control for a class of nonlinear uncertain multiagent systems (English)
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11 July 2024
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In this paper, the multiple dynamic targets enclosing problem is addressed for the double-integral nonlinear MAS with system uncertainties. In comparison to previous works in [\textit{S. Shoja} et al., ``Surrounding control of nonlinear multi-agent systems with non-identical agents'', ISA Trans. 70, 219--227 (2017)] and [\textit{A. Sharghi} et al., Nonlinear Dyn. 96, No. 3, 1795--1804 (2019; Zbl 1437.93005)], which only discuss first-order linear target dynamics and single-integral nonlinear MAS without system uncertainty, it is evident that the proposed control strategy is more comprehensive and holds greater potential in practical applications. The inclusion of system uncertainties poses significant challenges in designing the enclosing control protocol and conducting stability analysis. To deal with this problem, the system uncertainty is considered as an augmented state, establishing an augmented system to alleviate and compensate for the uncertainty effect and facilitating control protocol design. This approach reduces the need for the prior information about the system model, whose effectiveness is ensured through rigorous analysis. Considering the retrieval of the enclosing formation reference beacon, we develop a distributed estimator that employs the signum function to recover the enclosing formation centroid accurately by minimizing the errors between the actual state and estimated states. It should be noted that only incomplete information of multiple nonlinear targets is utilized.
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enclosing control
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nonlinear multiagent systems
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distributed estimation
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system uncertainties
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