Design of an evolving Fuzzy-PID controller for optimal trajectory control of a 7-DOF redundant manipulator with prioritized sub-tasks

Abstract Articulated manipulators constitute a major fraction of industrial robots. With the increase in the need to perform complex tasks requiring a higher degree of accuracy, such manipulators require a more robust and efficient control. In this paper, an evolving Fuzzy-PID control design for the trajectory tracking problem of a redundant 7-DOF serial manipulator is proposed. The scaling factors of the Fuzzy controller are evolved over time by using recent meta-heuristic techniques, namely, Moth-Flame Optimisation (MFO), Novel Bat Algorithm (NBA) and Sine Cosine Algorithm (SCA). The proposed technique which utilizes Intelligent control methods combined with meta-heuristics provides a promising hybrid control design, which has been found to be more efficient in our software implementation, in terms of reduced tracking error of the manipulator for its kinematic control in the joint space as compared to other controllers of the same nature that are generally used in practise. The performance of the controller is compared in the time-domain responses under external disturbances and have been found to outperform standard controllers without the need of any additional training.