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On Motion Planning and Control for Partially Differentially Flat Systems

Published online by Cambridge University Press:  16 July 2020

Yang Bai Open the ORCID record for Yang Bai [Opens in a new window] ,
Mikhail Svinin Open the ORCID record for Mikhail Svinin [Opens in a new window] ,
Evgeni Magid Open the ORCID record for Evgeni Magid [Opens in a new window]  and
Yujie Wang Open the ORCID record for Yujie Wang [Opens in a new window]
Yang Bai*
Affiliation:
Information Science and Engineering Department, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga525-8577, Japan. E-mail: svinin@fc.ritsumei.ac.jp
Mikhail Svinin
Affiliation:
Information Science and Engineering Department, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga525-8577, Japan. E-mail: svinin@fc.ritsumei.ac.jp
Evgeni Magid
Affiliation:
Department of Intelligent Robotics, Kazan Federal University, Kremlyovskaya str. 35, Kazan420008, Russian Federation. E-mail: magid@it.kfu.ru
Yujie Wang
Affiliation:
Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana-Champaign, IL, USA. E-mail: yujiew4@illinois.edu
*
*Corresponding author. E-mail: yangbai@fc.ritsumei.ac.jp
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Summary

This paper deals with motion planning and control problems for a class of partially differentially flat systems. They possess a feature that the derivative of the fiber variable can be represented purely by the base variable and its derivatives. Based on this feature, a Beta function-based motion planning algorithm is proposed with less computational cost compared with the optimal control formulation while providing similar system performance. Then, an adaptive controller is constructed through a function approximation technique-based approach. Finally, the feasibility of the proposed motion planning and control algorithms is verified by simulations.

Keywords

Motion planning and controlUnderactuated systemsPartial differential flatness
Type
Articles
Information
Robotica , Volume 39 , Issue 4 , April 2021 , pp. 718 - 734
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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