TY - GEN
T1 - Two-sided time domain order reduction methods for linear control systems
AU - Wang, Xiaolong
AU - Jiang, Yaolin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/14
Y1 - 2016/12/14
N2 - Large scale control systems appear in many areas of applications so that the direct simulation and synthesis of such systems is extremely time-consuming. Model order reduction has become an essential tool to enable a fast numerical simulation in practice. In this paper, we investigate two-sided model reduction methods for linear systems in the time domain, which are in contrast to the current one-sided methods. Based on Chebyshev polynomials, the Chebyshev coefficients for the higher derivatives of system outputs are derived. With the aid of the specific structures of such Chebyshev coefficients, reduced models are produced in a two-sided projection framework, which preserve the information both of the time and the frequency domain simultaneously, thereby providing a superior approximation compared to the one produced by onesided methods. The efficiency of our approach is verified by using a numerical example.
AB - Large scale control systems appear in many areas of applications so that the direct simulation and synthesis of such systems is extremely time-consuming. Model order reduction has become an essential tool to enable a fast numerical simulation in practice. In this paper, we investigate two-sided model reduction methods for linear systems in the time domain, which are in contrast to the current one-sided methods. Based on Chebyshev polynomials, the Chebyshev coefficients for the higher derivatives of system outputs are derived. With the aid of the specific structures of such Chebyshev coefficients, reduced models are produced in a two-sided projection framework, which preserve the information both of the time and the frequency domain simultaneously, thereby providing a superior approximation compared to the one produced by onesided methods. The efficiency of our approach is verified by using a numerical example.
KW - Chebyshev polynomials
KW - Krylov subspace
KW - Markov parameters
KW - Model reduction
UR - https://www.scopus.com/pages/publications/85010754900
U2 - 10.1109/CCSSE.2016.7784368
DO - 10.1109/CCSSE.2016.7784368
M3 - 会议稿件
AN - SCOPUS:85010754900
T3 - Proceedings of 2016 2nd International Conference on Control Science and Systems Engineering, ICCSSE 2016
SP - 128
EP - 132
BT - Proceedings of 2016 2nd International Conference on Control Science and Systems Engineering, ICCSSE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Control Science and Systems Engineering, ICCSSE 2016
Y2 - 27 July 2016 through 29 July 2016
ER -