Journal of Shanghai University(Natural Science Edition) ›› 2021, Vol. 27 ›› Issue (1): 59-77.doi: 10.12066/j.issn.1007-2861.2114

• Research Articles • Previous Articles     Next Articles

Model reduction of linear fast periodically switched systems using balanced truncation

DU Xin1(), HU Zheng1, WANG Jianying2   

  1. 1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China
    2. Computer Center, Shanghai University, Shanghai, 200444, China
  • Received:2018-12-26 Online:2021-02-28 Published:2021-02-28
  • Contact: DU Xin E-mail:duxn@shu.edu.cn

Abstract:

This study examines the model order reduction of linear fast periodically switched systems within the framework of a balanced truncation approach. The direct current (DC) averaged state-space model is introduced to describe the averaged dynamics of the given periodically switched systems in the presence of a DC input signal. In addition, a balanced truncation-based algorithm is developed to generate the desired reduced periodically switched model. A small-signal averaged state-space model is introduced to deal with cases in which the alternating current input signal is included. Similarly, an algorithm to generate the desired reduced model is proposed by exploiting the singular perturbation-type balanced truncation. Finally, numerical and experimental examples are presented to illustrate the effectiveness of the proposed results.

Key words: model reduction, periodically switched system, averaged model, small-signal average model, balanced truncation

CLC Number: