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Nash-optimization distributed model predictive control for multi mobile robots formation

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Abstract

This paper investigates the distributed model predictive control (DMPC) problem for multi mobile robots. The distributed system model is obtained by the kinematic model of single mobile robot. By including the coupling terms in the cost function, cooperation between subsystems can be incorporated in the distributed control problem. Then, each robot has its own optimal control problem, and neighboring subsystems can exchange information with one another by using wireless communication. The distributed model predictive control problem is formulated by the local cost function and solved by using Nash-optimization algorithm. The convergence condition of the proposed algorithm is presented. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.

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Acknowledgments

The work was supported partly by the National Natural Science Foundation of China under Grants No. 61304040 and 61403344, the Zhejiang Provincial Natural Science Foundation of China under Grant No. LZ15F030003, and the Hong Kong Scholars Program (XJ2015040).

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Correspondence to Andong Liu.

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Liu, A., Zhang, R., Zhang, Wa. et al. Nash-optimization distributed model predictive control for multi mobile robots formation. Peer-to-Peer Netw. Appl. 10, 688–696 (2017). https://doi.org/10.1007/s12083-016-0479-7

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  • DOI: https://doi.org/10.1007/s12083-016-0479-7

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