2018/06/28 by Klajdi Sinani, Serkan Gugercin, Sinani, Klajdi +1
Decision Sciences · Engineering · Physics and Astronomy · #Control Systems and Identification #Dynamical Systems (math.DS) #FOS: Electrical engineering #FOS: Mathematics #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1806.10797
openalex publication_date 2018/06/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we establish the interpolatory model reduction framework for optimal approximation of MIMO dynamical systems with respect to the H2 norm over a finite-time horizon, denoted as the H2(tf) norm. Using the underlying inner product space, we derive the interpolatory first-order necessary optimality conditions for approximation in the H2(tf) norm. Then, we develop an algorithm, which yields a locally optimal reduced model that satisfies the established interpolation-based optimality conditions. We test the algorithm on various numerical examples to illustrate its performance.