Sliding Mode Formation Optimization for Multi-Agent Systems With Unknown Disturbances in Predefined Time

WU Hao; GUO Liuxiao; ZHANG Jiancheng

doi:10.21656/1000-0887.450303

Volume 47 Issue 4

Apr. 2026

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Article Navigation > Applied Mathematics and Mechanics > 2026 > 47(4): 426-439

WU Hao, GUO Liuxiao, ZHANG Jiancheng. Sliding Mode Formation Optimization for Multi-Agent Systems With Unknown Disturbances in Predefined Time[J]. Applied Mathematics and Mechanics, 2026, 47(4): 426-439. doi: 10.21656/1000-0887.450303

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Sliding Mode Formation Optimization for Multi-Agent Systems With Unknown Disturbances in Predefined Time

doi: 10.21656/1000-0887.450303

School of Science, Jiangnan University, Wuxi, Jiangsu 214000, P.R.China

Funds:

The National Science Foundation of China(61973137

61807016)

Received Date: 2024-11-07
Rev Recd Date: 2025-02-26

Available Online: 2026-04-30

Abstract

Abstract

For leader-less multi-agent systems, the problem of distributed formation optimization in predefined time under unknown disturbances was studied, and the global cost function composed of local strongly convex functions for all agents was minimized. A class of formation optimization algorithms based on the sliding mode control was proposed to realize the formation control of multi-agent systems within the predefined time. The algorithm was divided into 3 parts: firstly, the integrated sliding mode control strategy was used to guide each agent to approach the sliding mode surface in the predefined time, and the external interference was effectively suppressed; then, the design protocol control was employed to guide each agent state to the minimum point of its local cost function; finally, the leaderless formation was realized for all agents to reach the minimum point of the global cost function. The algorithm does not require agents to share the gradients and Hessian matrix information of neighbors, thus saving the information exchange cost, and can deal with highly nonlinear multi-valued strongly convex cost functions. Several examples of numerical experiments demonstrate the effectiveness and reliability of the design control protocol algorithm.
- multi-agent system,
- distributed optimization,
- formation control,
- predefined time,
- sliding mode control

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References(30)

References

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