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Model Order Reduction of Nonlinear Models based on Decoupled Multi-model via Trajectory Piecewise Linearization

Seyed Saleh Mohseni, Mohamad Javad Yazdanpanah*, and Abolfazl Ranjbar Noei
International Journal of Control, Automation, and Systems, vol. 15, no. 5, pp.2088-2098, 2017

Abstract : "In this paper a novel model order reduction method for nonlinear models, based on decoupled multimodel, via trajectory piecewise-linearization is proposed. Through different strategies in trajectory piecewiselinear model reduction, model order reduction of a trajectory piecewise-linear model based on output weighting (TPWLOW), has been developed by authors of current work. The structure of mentioned work was founded based on Krylov subspace method, which is appropriate for high order models. Indeed the size of the Krylov subspaces may increase with the number of inputs of the system. As a result, the use of Krylov subspace method may become deficient the case for multi-input systems of order few decades. This paper aims to generalize the idea of model reduction of TPWLOW model by concentrating on balanced truncation technique which is appropriate for medium size systems. In addition, the proposed method either guarantees or provides guaranteed stability in some mentioned conditions. Finally, applicability of the reduced model, instead of high-order decoupled multi-model in weighting multi-model controllers, is investigated through the control of a nonlinear Alstom gasifier benchmark."

Keyword : "Balanced truncation, decoupled multi-model, model order reduction, nonlinear system, trajectory piecewise-linearization based on output weighting"

 
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