An Approach for Globalized H2-Optimal Model Reduction⁎. Issue 2 (2018)

• Record Type: Journal Article
• Authors: Castagnotto, Alessandro; Hu, Siyang; Lohmann, Boris
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 2(2018)
• Page Start: 196
• Page End: 201
• Publication Date: 2018
• Subjects: Minisymposium on Model Reduction -- model reduction -- model approximation -- large-scale systems -- MIMO -- global optimization; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.03.034
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In this contribution, we present a model order reduction algorithm for linear systems with multiple inputs and multiple outputs that aims at finding the global optimal reduced model of prescribed order n, with respect to the H 2 norm. Our approach is based on globalized local optimization, which requires a global sampling of the search space and subsequent local H 2 optimization. The increased cost resulting from repeated H 2 optimization will be mitigated by exploiting the Model Function framework for H 2 -optimal model reduction, making the optimization cost negligible compared to the cost of reduction. Numerical investigations motivate the need for globalized approaches in H 2 -optimal reduction and demonstrate how our method is capable of finding global optima, at a far lower cost than running conventional H 2 -optimal reduction for different initial samples.