Adaptive Fractional PID Controller for Robot Manipulator

TL;DR

This paper introduces an adaptive fractional PID controller optimized with a genetic algorithm for robot manipulators, demonstrating robustness and improved convergence in simulation compared to traditional PID controllers.

Contribution

It presents a novel fractional adaptive PID controller optimized via genetic algorithms, validated through simulation on a two-link robot manipulator.

Findings

The FPID controller is robust in tracking tasks.

Simulation shows convergence to desired trajectories.

Compared to integer PID, FPID offers improved performance.

Abstract

A Fractional adaptive PID (FPID) controller for a robot manipulator will be proposed. The PID parameters have been optimized by Genetic algorithm. The proposed controller is found robust by means of simulation in a tracking job. The validity of the proposed controller is shown by simulation of two-link robot manipulator. The result then is compared with integer type adaptive PID controller. It is found that when error signals in the learning stage are bounded, the trajectory of the robot converges to the desired one asymptotically.