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Distributed Tracking Control of Uncertain Multiple Manipulators Under Switching Topologies Using Neural Networks

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Abstract

The distributed tracking control of a group of manipulators under switching directed topologies is studied. Each manipulator is modeled by the Euler-Lagrange dynamics which includes uncertainties and external disturbances. The proposed controller has the neural network approximation unit for compensating uncertainties and the robust term for counteracting external disturbances. It can be proved that when the communication topology switches among a set of graphes which have a spanning tree and have no loop structure, the final tracking error can be reduced as small as possible.

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Acknowledgement

This work was supported in part by the National Natural Science Foundation of China (Grants 61422310, 61370032, 71401189) and the Beijing Natural Science Foundation (Grant 4162066).

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Correspondence to Long Cheng .

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Cheng, L., Cheng, M., Yu, H., Deng, L., Hou, ZG. (2016). Distributed Tracking Control of Uncertain Multiple Manipulators Under Switching Topologies Using Neural Networks. In: Cheng, L., Liu, Q., Ronzhin, A. (eds) Advances in Neural Networks – ISNN 2016. ISNN 2016. Lecture Notes in Computer Science(), vol 9719. Springer, Cham. https://doi.org/10.1007/978-3-319-40663-3_27

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  • DOI: https://doi.org/10.1007/978-3-319-40663-3_27

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