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Application of adaptive neural network based interval type-2 fuzzy logic control on a nonlinear system

Application of adaptive neural network based interval type-2 fuzzy logic control on a nonlinear system,10.1109/ICCRD.2011.5763863,Umit Onen,Mete Kalyo

Application of adaptive neural network based interval type-2 fuzzy logic control on a nonlinear system  
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In this study, four adaptive neural network based fuzzy logic controllers (ANNFL) are designed and used as two controllers in terms of interval type-2 fuzzy logic control. The new controllers are called as adaptive neural network based interval type-2 fuzzy logic controller (ANNIT2FL) and applied to a rigid-flexible robot manipulator. Initially dynamic model of the manipulator is obtained by using Lagrange equations and assumed modes method. ANNFL controllers are used for tracking and vibration control of system. The training and testing data of ANNFLs are obtained from the conventional PD control of the manipulator system. The performances of four ANFLCs are tested for different type and different number of membership functions and combined to create two ANNIT2FL controllers. Finally simulation results are obtained according to rotation and vibration control performances of ANNIT2FL controllers. Results demonstrate the remarkable performance of the proposed control technique. Keywords-Neural network, fuzzy logic control; interval type-2, robot manipulator; flexible link; tracking control; vibration control
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