TY - GEN
T1 - Decentralized Fuzzy Control for Minimum and Non-minimum Phase of a Coupled Four-Tank System
AU - Bayona, Jhon
AU - Narvaez, Dante I.
AU - Alegria, Elvis J.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In this paper, a coupled four-tank MIMO process is controlled for its minimum and non-minimum phase based on the fuzzy control method. The model of this system has a multivariable zero, which can be moved along the real axis to set its system phase by adjusting two hydraulic valves. The location of the poles and zeros of a system directly influences its stability and control effort. The proposed control for this process is based on a three-block decentralized fuzzy logic control, where each one is specialized in an operating mode defined by the system phase. Therefore, this proposal is more computationally efficient than a single high-dimensional fuzzy controller. The design of the proposed fuzzy rules and membership functions are based on prior knowledge of the system. Simulation results show the performance for the three decentralized fuzzy controllers, so a useful control response that considers settling time, error band, and overshoot requirements, is achieved in both minimum and non-minimum phases of the system.
AB - In this paper, a coupled four-tank MIMO process is controlled for its minimum and non-minimum phase based on the fuzzy control method. The model of this system has a multivariable zero, which can be moved along the real axis to set its system phase by adjusting two hydraulic valves. The location of the poles and zeros of a system directly influences its stability and control effort. The proposed control for this process is based on a three-block decentralized fuzzy logic control, where each one is specialized in an operating mode defined by the system phase. Therefore, this proposal is more computationally efficient than a single high-dimensional fuzzy controller. The design of the proposed fuzzy rules and membership functions are based on prior knowledge of the system. Simulation results show the performance for the three decentralized fuzzy controllers, so a useful control response that considers settling time, error band, and overshoot requirements, is achieved in both minimum and non-minimum phases of the system.
KW - Decentralized control
KW - Four-tank process
KW - Fuzzy logic
KW - Non-minimum phase
UR - http://www.scopus.com/inward/record.url?scp=85135019901&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-08545-1_64
DO - 10.1007/978-3-031-08545-1_64
M3 - Conference contribution
AN - SCOPUS:85135019901
SN - 9783031085444
T3 - Smart Innovation, Systems and Technologies
SP - 652
EP - 662
BT - Proceedings of the 7th Brazilian Technology Symposium, BTSym 2021 - Emerging Trends in Systems Engineering Mathematics and Physical Sciences
A2 - Iano, Yuzo
A2 - Saotome, Osamu
A2 - Kemper Vásquez, Guillermo Leopoldo
A2 - Cotrim Pezzuto, Claudia
A2 - Arthur, Rangel
A2 - Gomes de Oliveira, Gabriel
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th Brazilian Technology Symposium, BTSym 2021
Y2 - 8 November 2021 through 10 November 2021
ER -