Hybrid Intelligent Controllers for Highly Accurate Trajectory Tracking of Manipulator

Abstract

Due to the lack of accurate knowledge of robotic manipulator model, the highly precise trajectory tracking cannot be obtained. Moreover in these modern times, multiple design control objectives cannot be met by single controller, hence; there is a need for having two or more controllers at a time. Hence, more powerful and effective systems can be made by combining these intelligent controllers. In this regard, evolutionary optimized advance intelligent controller naming, support vector machine (SVM) is presented and validated for the problem chosen. To the author’s best knowledge, these proposed ant colony optimized (ACO) optimized hybrid controllers (PID, SMC and SVM) have not been yet implemented for the motion control problem of robotic manipulator and hence are not found in the literature.

Keywords: Robotic manipulator, trajectory tracking, support vector machine, ant colony optimization, sliding mode controller

Cite this Article
G. Krishan, V.R. Singh. Hybrid Intelligent Controllers for Highly Accurate Trajectory Tracking of Manipulator. Trends in Electrical Engineering. 2017; 7(3): 17–30p.