Adaptive Optimal Trajectory Tracking Control for Four Flexible Joint Robot Manipulator

Abstract

The Swarm Intelligence Optimization Methods were widely used in science. Animals' swarming behaviour mainly inspires these methods. Conventional optimization for Harris Hawks (HHO) is a recent technique based on the hunting strategy of harris hawks. The parallelism technique was used in this study to try to improve the original version of the algorithm. The improved algorithm sets the parameters of two controllers designed to improve the 4-link flexible joint manipulator's dynamic performance. The integral sliding mode controller controls the flexible joints, and the adaptive output feedback tracking controller controls the rigid links. When the improved algorithm is tested on benchmark functions and compared to other optimization strategies. the results show that the improved algorithm is faster and more precise. The simulation results indicate the improved algorithm's capabilities, with an enhancement percentage of 76.72 percent for the first link and 70.91 percent for the first joint compared to the standard approach.