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Adaptive Control of Bilateral Teleoperation System with Compensatory Neural-Fuzzy Controllers
Rabah Mellah,Said Guermah,Redouane Toumi 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.4
This paper presents two adaptive neural-fuzzy controllers equipped with compensatory fuzzy control inorder to adjust membership functions, and as well to optimize the adaptive reasoning by using a compensatorylearning algorithm. To the first controller is applied compensatory neural-fuzzy inference (CNFI) and to the secondcompensatory adaptive neural fuzzy inference system (CANFIS). Each controller is incorporated into a two channelbilateral teleoperation architecture involving force-position scheme, which combines the position control of theslave system with force reflection on the master. An analysis of stability and transparency based on a passivityframework is carried out. The resulting controllers are implemented on a one degree of freedom teleoperationsystem actuated by DC motors. The experimental results obtained show a fairly high accuracy in terms of positionand force tracking, under free space motion and hard contact motion, what highlights the effectiveness of theproposed controllers.