TY - GEN
T1 - Genetic-Algorithm-Based Tuning of PID Controllers for a Multipurpose Water Tank Plant
AU - Bautista Cama, J. L.F.
AU - Jara Alegria, E. O.
AU - Inga Narvaez, D.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Genetic algorithms
KW - PID controller
KW - metaheuristics
KW - multipurpose plant
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=85179881158&partnerID=8YFLogxK
U2 - 10.1109/INTERCON59652.2023.10326088
DO - 10.1109/INTERCON59652.2023.10326088
M3 - Conference contribution
AN - SCOPUS:85179881158
T3 - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
BT - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
Y2 - 2 November 2023 through 4 November 2023
ER -