TY - GEN
T1 - An infinite model predictive controller for multi input nonlinear processes
AU - Abu-Ayyad, Ma'Moun
AU - Abdessameud, Abdelkader
AU - Abu-Mahfouz, Issam
N1 - Publisher Copyright:
© 2017 ASME.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2017
Y1 - 2017
N2 - This paper presents a novel algorithm of an infinite model predictive controller for controlling nonlinear multi-input multioutput (MIMO) processes. The new strategy uses a set of continuous nonlinear functions that captures the nonlinear characteristics of the MIMO plant over a wide operating range resulting in a more accurate prediction of the controlled variables. The method formulates a nonlinear dynamic matrix that is manipulated variable dependent during closed-loop control. The proposed algorithm was implemented on a nonlinear MIMO thermal system comprising of three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (DMC) with improved results for various setpoint trajectories. The MIMO process has nonlinear parameters such as process gain and time constant that are dependent on the size of the control actions. Good disturbance rejection was attained resulting in improved tracking of multi-setpoint profiles in comparison to multi-model DMC.
AB - This paper presents a novel algorithm of an infinite model predictive controller for controlling nonlinear multi-input multioutput (MIMO) processes. The new strategy uses a set of continuous nonlinear functions that captures the nonlinear characteristics of the MIMO plant over a wide operating range resulting in a more accurate prediction of the controlled variables. The method formulates a nonlinear dynamic matrix that is manipulated variable dependent during closed-loop control. The proposed algorithm was implemented on a nonlinear MIMO thermal system comprising of three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (DMC) with improved results for various setpoint trajectories. The MIMO process has nonlinear parameters such as process gain and time constant that are dependent on the size of the control actions. Good disturbance rejection was attained resulting in improved tracking of multi-setpoint profiles in comparison to multi-model DMC.
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U2 - 10.1115/IMECE201770401
DO - 10.1115/IMECE201770401
M3 - Conference contribution
AN - SCOPUS:85040992245
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Dynamics, Vibration, and Control
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2017 International Mechanical Engineering Congress and Exposition, IMECE 2017
Y2 - 3 November 2017 through 9 November 2017
ER -