Abstract:
PID controllers for industrial processes have been usually tuned by methods such as Ziegler-Nichols, Cohen-Coon, frequency-based, root-locus-based and many others. Metahe...Show MoreMetadata
Abstract:
PID controllers for industrial processes have been usually tuned by methods such as Ziegler-Nichols, Cohen-Coon, frequency-based, root-locus-based and many others. Metaheuristic methods including genetic algorithms can optimize parameters to minimize cost functions, thus these techniques can be also used to tune PID controllers. The present study focuses on the design of PID controllers tuned by a simplified genetic algorithm for a multipurpose water tank plant in Peru, in order to optimize the parameters and improve its performance for single-loop and multi-loop control. For this purpose, the experimentally obtained transfer functions of the industrial multi-input multi-output plant are utilized, and a simplified genetic algorithm is proposed. It is demonstrated that in most of the cases, the PID gains obtained by the genetic algorithm compared to pid-tune tool of Matlab is superior according to the performance indexes in flow, pressure, level and temperature loops.
Published in: 2023 IEEE XXX International Conference on Electronics, Electrical Engineering and Computing (INTERCON)
Date of Conference: 02-04 November 2023
Date Added to IEEE Xplore: 23 November 2023
ISBN Information: