Sebastian, Anish (Idaho State University), Schoen, Marco (Idaho State University)

Hybrid Particle Swarm – Tabu Search Optimization Algorithm for Parameter Estimation

Scheduled for presentation during the Contributed session "Cooperative and Networked Control" (TuAT2), Tuesday, October 22, 2013, 10:35−10:55, Room 123

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on April 25, 2024

Abstract

A hybrid intelligent algorithm is proposed. The algorithm utilizes a particle swarm and a Tabu search algorithm. Swarm based algorithms and single agent based algorithms each, have distinct advantages and disadvantages. The goal of the presented work is to combine the strengths of the two different algorithms in order to achieve a more effective optimization routine. The developed hybrid algorithm is tailored such that it has the capability to adapt to the given cost function during the optimization process. The proposed algorithm is tested on a set of different benchmark problems. In addition, the hybrid algorithm is utilized for solving the estimation problem encountered for estimating the finger force output given a surface electromyogram (sEMG) signal at the input. This estimation problem is commonly encountered while developing a control system for a prosthetic hand.