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Article type: Research Article
Authors: Zhen, Shengchaoa; * | Huang, Kanga | Sun, Haoa | Zhao, Hana | Chen, Ye-Hwab
Affiliations: [a] School of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei, Anhui, PR China | [b] The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
Correspondence: [*] Correspondence to: Shengchao Zhen, School of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei, Anhui 230009, PR, China. Tel.: +86 15955120848; E-mail: zhenshengchao@qq.com.
Abstract: A novel and systematic approach for dynamic modeling and approximate constraint-following servo control of constrained mechanical systems under uncertainty is proposed. Fundamental equation of constrained mechanical systems is first obtained based on Udwadia-Kalaba approach which is applicable to holonomic and nonholonomic constrained systems no matter whether they satisfy the D’Alember’s principle. The uncertainty (possibly fast time-varying) in mechanical systems is bounded and the bound is unknown. Fuzzy set theory is used to describe the unknown bound. The performance requirement is modeled as servo constraints in second-order form. A model-based robust control is presented to approximately follow the servo constraints. The proposed control is deterministic and is not IF-THEN rules-based. The uniform boundedness and uniform ultimate boundedness of the tracking error are guaranteed, regardless of the uncertainty. A performance index (the combined cost, which includes average fuzzy system performance and control effort) is proposed based on the fuzzy information. The optimal design problem associated with the control can then be solved (explicitely or numerically) by minimizing the performance index. The resulting control design is systematic and is able to guarantee the deterministic performance as well as minimizing the cost.
Keywords: Mechanical system, fundamental equation, constraint, robust control, coordinated robot
DOI: 10.3233/IFS-151545
Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 777-789, 2015
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