Pareto design of state feedback tracking control of a biped robot via multiobjective PSO in comparison with sigma method and genetic algorithms: modified NSGAII and MATLAB's toolbox.
An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjec...
| Publicado en: | Scientific World Journal pp. 303101 - 303102 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103812856&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103812856 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103812856 103812856 NLM24616619 2012505210 10.1155/2014/303101 NLM24616619 PMC3927564 103812856 ppf: 303101 ppct: 1 formats: tig: atl: Pareto design of state feedback tracking control of a biped robot via multiobjective PSO in comparison with sigma method and genetic algorithms: modified NSGAII and MATLAB's toolbox. aug: au: Mahmoodabadi, M J Taherkhorsandi, M Bagheri, A affil: Department of Mechanical Engineering, Sirjan University of Technology, Sirjan, Iran. sug: subj: Algorithms Robotics Equipment Design Genetics ab: An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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