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Reduced order modelling and predictive control of multivariable nonlinear process
Authors: Abraham Anuj | Pappa N. | Honc Daniel | Sharma Rahul
Year: 2018
Type of publication: článek v odborném periodiku
Name of source: Sadhana-Academy proceedings in engineering sciences
Publisher name: Indian Academy of Sciences
Place: Bangalore
Page from-to: nestránkováno
Titles:
Language Name Abstract Keywords
cze Modelování redukovaným řádem a prediktivní řízení nelineárních vícerozměrných procesů V příspěvku je prezentována účinná prediktivní strategie řízení, kterou lze aplikovat na komplexní vícerozměrné procesy. Prediktivní řízení; destilační kolona; model s redukovaným řádem; dominantní pól; klastering
eng Reduced order modelling and predictive control of multivariable nonlinear process In this paper, an efficient model-predictive control strategy that can be applied to complex multivariable process is presented. A reduced order generalized predictive algorithm is proposed for online applications with reduction in complexity and time elapsed. The complex multivariable process considered in this work is a binary distillation column. The reduced order model is developed with a recently proposed hybrid algorithm known as Clustering Dominant Pole Algorithm and is able to compute the full set of dominant poles and their cluster centre efficiently. The controller calculates the optimal control action based on the future reference signals, current state and constraints on manipulated and controlled variables for a high-order dynamic simulated model of nonlinear multivariable binary distillation column process. The predictive control algorithm uses controlled auto-regressive integrated moving average model. The performance of constraint generalized predictive control scheme is found to be superior to that of the conventional PID controller in terms of overshoot, settling time and performance indices, mainly ISE, IAE and MSE. Predictive control; distillation column; reduced order model; dominant pole; clustering

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