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Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 42-234
Full Name: Wael Elawady
Position: Doctor (Researcher)
Age: ON
Sex: Male
Address: egypt-tanta university-faculty of engineering
Country: EGYPT
Tel: 0105048674
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E-mail address: wmeana2007@yahoo.com
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Title of the Paper: Fuzzy Self-Tuning Fuzzy Precompensation Inverse Dynamics
Authors as they appear in the Paper: A. F. Amer , E. A. Sallam, and W. M. Elawady
Email addresses of all the authors: aamer@aast.edu, sallam_9@hotmail.com, wmeana2007@yahoo.com
Number of paper pages: 10
Abstract: Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. inverse dynamics control is a well-known conventional motion control strategy for manipulators which ensures global asymptotic stability for fixed symmetric positive definite (proportional and derivative) gain matrices. To enhance the inverse dynamics controller performance for the control of rigid planar robot manipulators, in this paper, a fuzzy precompensation of a hybrid fuzzy inverse dynamics controller is proposed. The proposed control scheme consists of a fuzzy logic-based precompensator followed by a hybrid fuzzy inverse dynamics controller. The hybrid fuzzy control is a supervisory hierarchical fuzzy controller (SHFC) for tuning the Proportional and Derivative gains of the conventional controller according to the actual tracking position error and the actual tracking velocity error. The hierarchical contr!
ol scheme of the hybrid fuzzy controller consists of an intelligent upper level supervisory fuzzy controller and a lower level direct conventional PD controller. The upper level controller provides a mechanism to the main goal of the system and the lower level controller delivers the solutions to a particular situation. Numerical simulations using the dynamic model of three DOF planar rigid robot manipulator with uncertainties show the effectiveness of the approach in trajectory tracking problems. Performance indices i.e. integral absolute error (IAE) and integral time multiplied absolute error (ITAE) are used for comparison. Our results show that precompensation of a hybrid fuzzy inverse dynamics controller have superior performance compared to a conventional inverse dynamics controller.
Keywords: uncertainties, supervisory hierarchical fuzzy controller (SHFC), robots,
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