Model Approximation in Multiparametric Optimization and Control A Computational Study
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2018 Elsevier B.V. Incorporating a high fidelity model that accurately describes a dynamical system in an optimization and control study may often lead to an intractable formulation, hence the use of model approximation is required. This computational study closely examines various approximation techniques in the context of multiparametric optimization and control with the use of key error metrics including: (i) open loop comparison of the high fidelity and approximate model, (ii) verification of step response profiles, and (iii) comparison of key features of the feasible space and objective function in the optimization formulation. Two systems are used as a basis for this study: a tank system utilized to highlight the main principles of this approach, and a Continuously Stirred Tank Reactor (CSTR) where the reaction mechanisms are manipulated to increase the model complexity.