Abstract
Highly precise tracking of a robotic manipulator in presence of uncertainties like noise, disturbances, and friction has been addressed in this particular paper. An integrated proportional derivative and support vector machine (SVMPD) controller has been proposed for manipulator tracking. To illustrate the efficiency of the proposed controller, simulations have been done on a 2-DOF manipulator system. Performance of the proposed controller has been checked and verified with respect to to a simple PID controller and the radial bias neural network proportional integral derivative (RBNNPD) controller. It has been proved that the proposed controller can achieve better tracking performance as compared to other controllers as the range of errors is less and the time taken by the controller has reduced up to 14 times as compared to RBNN.
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