Moment Matching Based Model Reduction for LPV State-Space Models

2015/08/14 by Bastug, Mert, Petreczky, Mihaly, Toth, Roland +3 · 1 citation
#FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.1508.03446

Abstract

We present a novel algorithm for reducing the state dimension, i.e. order, of linear parameter varying (LPV) discrete-time state-space (SS) models with affine dependence on the scheduling variable. The input-output behavior of the reduced order model approximates that of the original model. In fact, for input and scheduling sequences of a certain length, the input-output behaviors of the reduced and original model coincide. The proposed method can also be interpreted as a reachability and observability reduction (minimization) procedure for LPV-SS representations with affine dependence.

Cited by

• Tensor-based reduction of linear parameter-varying state-space models

Related

• Reduced-order modeling of LPV systems in the Loewner framework
• Realization Theory for LPV State-Space Representations with Affine Dependence
• Tensor-based reduction of linear parameter-varying state-space models
• Model reduction for LPV systems based on approximate modal decomposition
• Minimal realizations of input-output behaviors by LPV state-space representations with affine dependency