Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Neural-Network-based Consensus Tracking of Second-Order Multi-Agent Systems With Unknown Heterogeneous Nonlinearities

미지의 이종 비선형성을 갖는 2차 비선형 다개체 시스템의 신경 회로망 기반 일치 추종

  • Choi, Yun Ho (School of Electrical and Electronics Engineering, Chung-Ang University) ;
  • Yoo, Sung Jin (School of Electrical and Electronics Engineering, Chung-Ang University)
  • 최윤호 (중앙대학교 전자전기공학과) ;
  • 유성진 (중앙대학교 전자전기공학과)
  • Received : 2016.04.18
  • Accepted : 2016.05.09
  • Published : 2016.06.01
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Abstract

This paper presents a simple approximation-based design approach for consensus tracking of heterogeneous second-order nonlinear systems under a directed network. All nonlinearities of followers are assumed to be unknown and non-identical. In the controller design procedure, graph-independent error surfaces are used and an unimplementable intermediate controller for each follower is designed at the first design step. Then, by adding and subtracting a graph-based term at the second step, the actual controller for each follower is designed by using one neural network employed to estimate a lumped and distributed nonlinearity. Therefore, the proposed local controller for each follower has a simpler structure than existing approximation-based consensus tracking controllers for multi-agent systems with unmatched nonlinearities.

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References

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