TY - GEN
T1 - Artificial Bee Colony Optimization Approach for an Adaptive Fuzzy Sliding Mode Controller in a pH Neutralization Reactor
AU - Espin, Jorge
AU - Estrada, Sebastian
AU - Benitez, Diego S.
AU - Camacho, Oscar
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This work presents an adaptive sliding mode controller based on Takagi and Sugeno's (TS) fuzzy models and Smith predictor concepts optimized by the artificial bee colony algorithm. In order to test the proposed control scheme, a pH neutralization reactor was modeled using experimental methods around different operating points. Several reference changes are used to test the proposed approach against the traditional PID approach and the sliding mode controller combined with the TS fuzzy model. Performance metrics are used for quantitative comparison.
AB - This work presents an adaptive sliding mode controller based on Takagi and Sugeno's (TS) fuzzy models and Smith predictor concepts optimized by the artificial bee colony algorithm. In order to test the proposed control scheme, a pH neutralization reactor was modeled using experimental methods around different operating points. Several reference changes are used to test the proposed approach against the traditional PID approach and the sliding mode controller combined with the TS fuzzy model. Performance metrics are used for quantitative comparison.
KW - Adaptive Control
KW - Artificial Bee Colony algorithm
KW - Sliding Mode Control
KW - Takagi-Sugeno fuzzy systems
UR - http://www.scopus.com/inward/record.url?scp=85142383009&partnerID=8YFLogxK
U2 - 10.1109/ARGENCON55245.2022.9939781
DO - 10.1109/ARGENCON55245.2022.9939781
M3 - Contribución a la conferencia
AN - SCOPUS:85142383009
T3 - 2022 IEEE Biennial Congress of Argentina, ARGENCON 2022
BT - 2022 IEEE Biennial Congress of Argentina, ARGENCON 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Biennial Congress of Argentina, ARGENCON 2022
Y2 - 7 September 2022 through 9 September 2022
ER -