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۱Comparison QFT Controller Based on Genetic Algorithm with MIMO Fuzzy Approach in a Robot
اطلاعات انتشار: پنجمین کنفرانس بین المللی پیشرفتهای علوم و تکنولوژی، سال
تعداد صفحات: ۸
In this paper, a practical method to design a robust controller for a two–arm manipulator using Quantitative Feedback Theory (QFT) using GA is proposed. Robot manipulators havemultivariable nonlinear transfer function, implementation of QFT technique requires first to convert its nonlinear plant into family of linear and uncertain plant sets and then an optimal robustcontroller will be designed for each set. In order to illustrate the utility of our algorithm we present the application of it to a two degree of freedom robot arm manipulator. In the presented method the controller is designed directly by choosing and optimization of coefficients of transfer function byusing genetic algorithm. In optimization procedure, stability and bounds of the system were considered as the constraints of the problem. Non–linear simulations on the tracking problem are performed and the results highlight the success of the designed controllers. The results indicatethat applying the proposed technique successfully overcomes the obstacles to robust control of non–linear a robot. Lastly designed controller with QFT method is compared with Fuzzy controller and it is shown that QFT technique suggests a controller which has a better control performance<\div>
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