Journal
ISA TRANSACTIONS
Volume 53, Issue 2, Pages 560-567Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2013.12.019
Keywords
Optimal tuning; Model predictive control; Particle swarm optimization; Robust control
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This paper describes the development of a method to optimally tune constrained MPC algorithms with model uncertainty. The proposed method is formulated by using the worst-case control scenario, which is characterized by the Monad resiliency index and the condition number, and a given nonlinear multi-objective performance criterion. The resulting constrained mixed-integer nonlinear optimization problem is solved on the basis of a modified version of the particle swarm optimization technique, because of its effectiveness in dealing with this kind of problem. The performance of this PSO-based tuning method is evaluated through its application to the well-known Shell heavy oil fractionator process. (C) 2013 ISA. Published by Elsevier Ltd. All rights reserved.
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