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Applications of switched reluctance motor (SRM) to direct drive robot are increasingly popular because of its valuable advantages. However, a greatest potential defect its torque ripple owing to the significant nonlinearities. In this paper, a fuzzy neural network (FNN) is applied to control the SRM torque at the goal of the torque-ripple minimization. The desired current provided by FNN model compensates...
In this paper, two different adaptive network based fuzzy logic controllers (Neuro-Fuzzy) are designed for trajectory tracking control of a 3-DOF scara type robot manipulator. The kinematic and the dynamic equations are used to obtain equations of motion of robot manipulator and three different rise functions are chosen for desired Cartesian trajectory as circular tool trajectory. The performances...
This paper deals with adaptive trajectory tracking for a five DOF robot manipulator, A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The applicability of the proposed scheme is illustrated...
This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators. A new control scheme is proposed based on neural network technology and linear feedback approach for tracking a planned trajectory. The control system is established with two parallel subsystems designed separately. One is a linear controller based on state feedback with...
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