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Decentralized control of collaborative redundant manipulators with partial command coverage via locally connected recurrent neural networks

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Abstract

This paper studies the decentralized control of multiple redundant manipulators for the cooperative task execution problem. Different from existing work with assumptions that all manipulators are accessible to the command signal, we propose in this paper a novel strategy capable of solving the problem even though there exists some manipulators unable to access the command signal directly. The cooperative task execution problem can be formulated as a constrained quadratic programming problem. We start analysis by re-designing the control law proposed in (Li et al. Neurocomputing, 2012), which solves the optimization problem recursively. By replacing the command signal with estimations with neighbor information, the control law becomes to work in the partial command coverage situation. However, the stability and optimality of the new system are not necessarily the same as the original system. We then prove in theory that the system indeed also globally stabilizes to the optimal solution of the constrained quadratic optimization problem. Simulations demonstrate the effectiveness of the proposed method.

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Acknowledgments

The authors would like to acknowledge the constant motivation and inspiration by the motto stating that “the only limit to our realization of tomorrow will be our doubts of today". The authors would like to acknowledge the support by the National Science Foundation of China under Grant NSFC: 61105090.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, 07030, USA

    Shuai Li

  2. School of Nursing, Sun Yat-Sen University, Guangzhou, Guangdong, China

    Hongzhu Cui

  3. Robot Sensor and Human-machine Interaction Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China

    Yangming Li

  4. Department of Computer Science, University of Massachusetts, Amherst, MA, 01003, USA

    Bo Liu

  5. School of Mechatronics and Information, Yiwu Industrial and Commercial College, Yiwu, Zhejiang, China

    Yuesheng Lou

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  1. Shuai Li
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  2. Hongzhu Cui
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Correspondence to Shuai Li.

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Li, S., Cui, H., Li, Y. et al. Decentralized control of collaborative redundant manipulators with partial command coverage via locally connected recurrent neural networks. Neural Comput & Applic 23, 1051–1060 (2013). https://doi.org/10.1007/s00521-012-1030-2

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  • DOI: https://doi.org/10.1007/s00521-012-1030-2

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