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The Robotic Impedance Controller Multi-objective Optimization Design Based on Pareto Optimality

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Intelligent Computing Methodologies (ICIC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9773))

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Abstract

The robotic impedance control is currently one of the main control methods, its main characteristic is that it can make manipulators move to the appointed position quickly and accurately. Due to the high complexity of the robot system, to adjust the impedance controller parameter is always difficult. The impedance controller multi-objective optimization design method is proposed, taking dynamic performances as the optimization objectives, a multi-objective optimization algorithm based on Pareto optimality is applied to the optimal design, obtain Pareto optimal solutions, and get some initial impedance controller adjustment rules, the satisfactory solution is selected in Pareto-optimal solutions according to the requirements of the present system. Simulation results indicate the effectiveness of the proposed algorithm.

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Acknowledgments

This research was supported by grants from The National Natural Science Fund (No. 61403175), Gansu Province Fundamental Research Funds (No. 2014), Gansu Province Basic Research Innovation Group Project (No. 1506RJIA031), Lanzhou University of Technology Hongliu Project Funds (No. Q201210).

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Authors and Affiliations

  1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China

    Erchao Li

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  1. Erchao Li
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Correspondence to Erchao Li .

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Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. Inha University , Incheon, Korea (Republic of)

    Kyungsook Han

  3. Liverpool John Moores University , Liverpool, United Kingdom

    Abir Hussain

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© 2016 Springer International Publishing Switzerland

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Li, E. (2016). The Robotic Impedance Controller Multi-objective Optimization Design Based on Pareto Optimality. In: Huang, DS., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2016. Lecture Notes in Computer Science(), vol 9773. Springer, Cham. https://doi.org/10.1007/978-3-319-42297-8_39

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  • DOI: https://doi.org/10.1007/978-3-319-42297-8_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42296-1

  • Online ISBN: 978-3-319-42297-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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