Comparison of Bioinspired Optimization Techniques for Improving the Performance of Dynamic Sliding Mode Controllers

Jorge Espin, Sebastian Estrada, Diego Benitez, Oscar Camacho

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Bio-inspired optimization algorithms have been shown in recent years to produce optimal solutions to various complex computational issues in science and engineering. This paper presents a comparative examination of bio-inspired algorithms to better understand and measure their efficacy in searching for the best tuning parameters for a Dynamical Sliding Mode Control for integrating systems with an inverse response and dead time. The comparative analysis includes four bioinspired algorithms: particle swarm optimization, artificial bee colony, ant colony optimization, and genetic algorithms, and how they can improve the performance of the controller by searching for optimum tuning parameter solutions. The parameters of each algorithm have different impacts on the searching mechanism and were evaluated in two simulated systems. Ant colony optimization shows a significant capability over other algorithms to find optimal solutions for our problem.

Idioma originalInglés
Título de la publicación alojada2022 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022 - Proceedings
EditoresAlvaro David Orjuela-Canon
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665474702
DOI
EstadoPublicada - 2022
Evento2022 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022 - Cali, Colombia
Duración: 27 jul. 202229 jul. 2022

Serie de la publicación

Nombre2022 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022 - Proceedings

Conferencia

Conferencia2022 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022
País/TerritorioColombia
CiudadCali
Período27/07/2229/07/22

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