An iterative scheme for finite horizon model reduction of continuous-time linear time-varying systems

2023/09/02 by Kasturi Das, Das, Kasturi, Srinivasan Krishnaswamy +3
Engineering · Physics and Astronomy · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #Model Reduction and Neural Networks #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2309.00921

openalex publication_date 2023/09/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we obtain the functional derivatives of a finite horizon error norm between a full-order and a reduced-order continuous-time linear time-varying (LTV) system. Based on the functional derivatives, first-order necessary conditions for optimality of the error norm are derived, and a projection-based iterative scheme for model reduction is proposed. The iterative scheme upon convergence produces reduced-order models satisfying the optimality conditions. Finally, through a numerical example, we demonstrate the better performance of the proposed model reduction scheme in comparison to the finite horizon balanced truncation algorithm for continuous-time LTV systems.

Related

• First and Second Order Optimal H₂ Model Reduction for Linear Continuous-Time Systems
• An Efficient Algorithm to Compute Norms for Finite Horizon, Linear Time-Varying Systems
• Finite-Frequency Model Order Reduction of Linear Systems via Parameterized Frequency-dependent Balanced Truncation
• A time domain a posteriori error bound for balancing-related model order reduction
• On frequency- and time-limited H2-optimal model order reduction