Single-input and single-output (SISO) controller reduction based on the $L_1$-norm
Single-input and single-output (SISO) controller reduction based on the $L_1$-norm
This paper proposes a new method to solve the controller-reduction problem based on the $L_1$-norm. This method uses a reduced-order closed-loop system to deduce reduced-order controllers. The problem of obtaining the required lower-order closed-loop system was formulated as an $L_1$-norm optimization, and the conditions were provided for guaranteeing the internal stability and the existence of lower-order controllers from the obtained reduced-order closed-loop system. In addition, the particle swarm optimization and sequence linear programming were adopted to solve the resultant $L_1$-norm optimization. Two numerical examples demonstrated the effectiveness of the proposed method.
688-694
Yang, Y.
f2e3049f-3750-4497-ba13-7a9072f4b562
Wu, J.
5a0119e5-a760-4ff5-90b9-ec69926ce501
Xiong, R.
c751cc9b-22c9-4995-be9b-ada79e026cf5
Xu, W.
367fce1d-4335-45cc-995c-5aa75de74278
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
November 2008
Yang, Y.
f2e3049f-3750-4497-ba13-7a9072f4b562
Wu, J.
5a0119e5-a760-4ff5-90b9-ec69926ce501
Xiong, R.
c751cc9b-22c9-4995-be9b-ada79e026cf5
Xu, W.
367fce1d-4335-45cc-995c-5aa75de74278
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Yang, Y., Wu, J., Xiong, R., Xu, W. and Chen, Sheng
(2008)
Single-input and single-output (SISO) controller reduction based on the $L_1$-norm.
Asia-Pacific Journal of Chemical Engineering, 3 (6), .
Abstract
This paper proposes a new method to solve the controller-reduction problem based on the $L_1$-norm. This method uses a reduced-order closed-loop system to deduce reduced-order controllers. The problem of obtaining the required lower-order closed-loop system was formulated as an $L_1$-norm optimization, and the conditions were provided for guaranteeing the internal stability and the existence of lower-order controllers from the obtained reduced-order closed-loop system. In addition, the particle swarm optimization and sequence linear programming were adopted to solve the resultant $L_1$-norm optimization. Two numerical examples demonstrated the effectiveness of the proposed method.
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APJCE-08.pdf
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Published date: November 2008
Organisations:
Southampton Wireless Group
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Local EPrints ID: 267030
URI: http://eprints.soton.ac.uk/id/eprint/267030
ISSN: 1932-2135
PURE UUID: f70a37e4-5511-48d5-92da-06137a0e346c
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Date deposited: 13 Jan 2009 13:09
Last modified: 11 Nov 2024 19:54
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Contributors
Author:
Y. Yang
Author:
J. Wu
Author:
R. Xiong
Author:
W. Xu
Author:
Sheng Chen
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