ICONIP 2017: Neural Information Processing pp 139-146 | Cite as

Consensus Maneuvering of Uncertain Nonlinear Strict-Feedback Systems

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10639)

Abstract

In this paper, a consensus maneuvering problem is investigated for uncertain nonlinear systems in strict-feedback form. Consensus maneuvering controllers are developed based on a modular design approach. Specifically, an estimation module is proposed, where a neural network is employed for approximating the unknown nonlinearities. Then, a controller module is designed based on a modified dynamic surface control method. Finally, the input-to-state stability of the close-loop system is analyzed via cascade theory, and the consensus maneuvering error is proved to converge to a residual set.

Keywords

Consensus maneuvering Strict-Feedback system Uncertain nonlinearity Modular design approach 
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Notes

Acknowledgments

The work of D. Wang was supported in part by the National Natural Science Foundation of China under Grants 61673081, and in part by the Fundamental Research Funds for the Central Universities under Grant 3132016313, and in part by the National Key Research and Development Program of China under Grant 2016YFC0301500. The work of Z. Peng was supported in part by the National Natural Science Foundation of China under Grants 51579023, and in part by the China Postdoctoral Science Foundation under Grant 2015M570247, and in part by High Level Talent Innovation and Entrepreneurship Program of Dalian under Grant 2016RQ036.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Marine EngineeringDalian Maritime UniversityDalianPeople’s Republic of China
  2. 2.Department of Computer ScienceCity University of Hong KongKowloon TongHong Kong

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