Optimal Improved Pid Controller With Goa Algorithm for Single Link Human Leg Robot

Abstract

A Human Leg Robot (HLR) is a type of manipulator robot that has non-linear, quality, time-varying behaviors and uncertainty in parameters. Therefore, it must be controlled. The purpose of this work is to design an optimal Improved Proportional-Integral-Derivative (IPID) controller for this robot to improve its performance in tracking the desired path. Two schemes of IPID controllers are suggested to enhance the performance of the traditional PID in controlling the human leg robot and following the desired path. The Grasshopper Optimization Algorithm (GOA) is considered to optimize the IPID parameters. The performance of the suggested IPID structures has been compared to traditional PID methods. The simulation results show that the efficiency of these schemes was enough to handle the tracking problems of the HLR.