TY - GEN
T1 - Fuzzy adaptive MPC for nonlinear time varying delayed systems
AU - Aboukheir, Hanna
AU - Herrera, Marco
AU - Chavez, Danilo
AU - Leica, Paulo
AU - Camacho, Oscar
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - In this work, a predictive controller based on fuzzy models is developed; first a fuzzy Takagi Sugeno ( T-S) model is proposed considering the input/output data, the measured disturbances and varying time delay of the system, with this information a fuzzy predictor is built in order to provide the future measures minimizing uncertainties. A modification of the cost function is proposed simplifying the controller calculation considerably, also providing a reconfigurable and stabilizing control law; the proposal is evaluated through simulations on a chemical process.
AB - In this work, a predictive controller based on fuzzy models is developed; first a fuzzy Takagi Sugeno ( T-S) model is proposed considering the input/output data, the measured disturbances and varying time delay of the system, with this information a fuzzy predictor is built in order to provide the future measures minimizing uncertainties. A modification of the cost function is proposed simplifying the controller calculation considerably, also providing a reconfigurable and stabilizing control law; the proposal is evaluated through simulations on a chemical process.
KW - Adaptive Systems
KW - Fuzzy Systems
KW - Nonlinear System Identification
KW - Predictive control
UR - https://www.scopus.com/pages/publications/85098560143
U2 - 10.1109/ANDESCON50619.2020.9272058
DO - 10.1109/ANDESCON50619.2020.9272058
M3 - Contribución a la conferencia
AN - SCOPUS:85098560143
T3 - 2020 IEEE ANDESCON, ANDESCON 2020
BT - 2020 IEEE ANDESCON, ANDESCON 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE ANDESCON, ANDESCON 2020
Y2 - 13 October 2020 through 16 October 2020
ER -