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Decentralized Robust Optimal Control for Modular Robot Manipulators Based on Zero-Sum Game with ADP

  • Bo DongEmail author
  • Tianjiao An
  • Fan Zhou
  • Shenquan Wang
  • Yulian Jiang
  • Keping Liu
  • Fu Liu
  • Huiqiu Lu
  • Yuanchun Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11555)

Abstract

In this paper, a decentralized robust zero-sum optimal control method is proposed for modular robot manipulators (MRMs) based on the adaptive dynamic programming (ADP) approach. The dynamic model of MRMs is formulated via joint torque feedback (JTF) technique that is deployed for each joint module, in which the local dynamic information is used to design the model compensation controller. An uncertainty decomposition-based robust control is developed to compensate the model uncertainties, and then the robust optimal control problem of MRMs with uncertain environments can be transformed into a two-player zero-sum optimal control one. According to the ADP algorithm, the Hamilton-Jacobi-Isaacs (HJI) equation is solved by constructing action-critic neural networks (NNs) and then the approximate optimal control policy derivation is possible. Experiments are conducted to verify the effectiveness of the proposed method.

Keywords

Modular robot manipulators Adaptive dynamic programming Optimal control Zero-sum game 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant nos. 61374051, 61773075 and 61703055) and the Scientific Technological Development Plan Project in Jilin Province of China (Grant nos. 20170204067GX, 20160520013JH and 20160414033GH).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bo Dong
    • 1
    • 2
    Email author
  • Tianjiao An
    • 1
  • Fan Zhou
    • 1
  • Shenquan Wang
    • 1
  • Yulian Jiang
    • 1
  • Keping Liu
    • 1
  • Fu Liu
    • 3
  • Huiqiu Lu
    • 3
  • Yuanchun Li
    • 1
  1. 1.Department of Control Science and EngineeringChangchun University of TechnologyChangchunChina
  2. 2.State Key Laboratory of Management and Control for Complex Systems, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.Department of Control Science and EngineeringJilin UniversityChangchunChina

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