Study of optimization methods for tuning of PID gains for three link manipulator

Abstract

Robotic manipulators are used in wide range of industrial applications. These are highly complex, multi-input multi-output and coupled systems requiring efficient control mechanism. This complexity is further enhanced as the number of links is increased. PID control is the most widely employed control scheme in the manufacturing industry but conventional tuning approaches for tuning PID gains do not offer satisfactory results for complex systems like robotic manipulators. This generates the need for advance optimization techniques to carry out the tuning of PID controller for a customized performance index. This paper presents a comparative study of the performances of three such heuristic optimization algorithms, namely. Teacher Learning Based Optimization Algorithm (TLBO), Flower Pollination Optimization Algorithm (FPO) and Genetic Algorithm (GA) for tuning the PID controllers applied to a three link planar rigid robotic manipulator. The trajectory tracking and disturbance rejection performances of the PID controller tuned by these algorithms are considered. The tuning has been done by minimizing the weighted sum of integral absolute error and integral of absolute controller output for path following. Based on the results obtained, it was concluded that TLBO offers superior results.