Adaptive simulated annealing for tuning PID controllers

Article type: Research Article

Authors: Fraga-Gonzalez, Luis Fernando^a | Fuentes-Aguilar, Rita Q.^a | Garcia-Gonzalez, Alejandro^a | Sanchez-Ante, Gildardo^{b; *}

Affiliations: [a] Tecnologico de Monterrey, Campus Guadalajara, Av. Gral Ramon Corona 2514, Zapopan, Jal 45201, Mexico | [b] Universidad Politecnica de Yucatan, Carretera Merida-Tetiz, Km. 4.5, Ucu, YUC 97357, Mexico

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: PID controllers are one of the most popular types of controllers found in the industry; they require determining three real values to minimize the error over time and to deal with specific process requirements. Finding such values has been subjected to extensive research, and many popular algorithms and methods exist to accomplish this. One of these methods is Simulated Annealing. In this paper, we study the use of the re-annealing characteristic of Adaptive Simulated Annealing (ASA) for PID tuning in 20 benchmark systems. This adaptive version gives special treatment to each parameter of the search space. We compare the results of ASA with a simple SA algorithm. An extra comparison, with a Particle Swarm Optimization algorithm, was made to provide some information on how ASA behaves compared against another optimization based method. The results show that using an adaptive algorithm effectively improves the performance of the tested systems.

Keywords: Adaptive Simulated Annealing, meta-heuristics, optimization, automatic control, PID controller

DOI: 10.3233/AIC-170741

Journal: AI Communications, vol. 30, no. 5, pp. 347-362, 2017