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Primary exploration of nonlinear information fusion control theory

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Abstract

By introducing information fusion techniques into a control field, a new theory of information fusion control (IFC) is proposed. Based on the theory of information fusion estimation, optimal control of nonlinear discrete control system is investigated. All information on control strategy, including ideal control strategy, expected object trajectory and dynamics of system, are regarded as measuring information of control strategy. Therefore, the problem of optimal control is transferred into the one of information fusion estimation. Firstly, the nonlinear information fusion estimation theorems are described. Secondly, an algorithm of nonlinear IFC theory is detailedly deduced. Finally, the simulation results of manipulator shift control are given, which show the feasibility and effectiveness of the presented algorithm.

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Authors and Affiliations

  1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Wang ZhiSheng, Wang DaoBo & Zhen ZiYang

Authors
  1. Wang ZhiSheng
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  2. Wang DaoBo
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  3. Zhen ZiYang
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Correspondence to Wang ZhiSheng.

Additional information

Supported by the National Natural Science Foundation of China (Grant No. 60673026)

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Wang, Z., Wang, D. & Zhen, Z. Primary exploration of nonlinear information fusion control theory. SCI CHINA SER F 50, 686–696 (2007). https://doi.org/10.1007/s11432-007-0049-y

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  • DOI: https://doi.org/10.1007/s11432-007-0049-y

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