Premium
Decentralized Control System Design under Uncertainty Using Mixed‐Integer Optimization
Author(s) -
Paramasivan G.,
Kienle A.
Publication year - 2012
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201100357
Subject(s) - benchmark (surveying) , mathematical optimization , fractionating column , heuristic , integer (computer science) , control theory (sociology) , controller (irrigation) , mathematics , selection (genetic algorithm) , variance (accounting) , nonlinear system , control (management) , computer science , distillation , artificial intelligence , chemistry , physics , geodesy , organic chemistry , accounting , quantum mechanics , agronomy , business , biology , programming language , geography
Decentralized control system design comprises the selection of a suitable control structure and controller parameters. In this contribution, the optimal control structure and the optimal controller parameters are determined simultaneously using mixed‐integer dynamic optimization (MIDO) under uncertainty, to account for nonlinear process dynamics and various disturbance scenarios. Application of the sigma point method is proposed in order to approximate the expectation and the variance of a chosen performance index with a minimum number of points to solve the MIDO problem under uncertainty. The proposed methodology is demonstrated with a benchmark problem of an inferential control for a reactive distillation column. The results are compared with established heuristic design methods and with previous deterministic approaches.