arrow
Return

Controller approximation:: Approaches for preserving H∞ performance

delete1998-07-01
delete51
PRE
AI
P
P.J. Goddard
K
K. Glover
DOI:10.1109/9.701085delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This paper investigates the design of reduced-order controllers using an H-infinity framework. Given a stabilizing controller which satisfies a prespecified level of closed-loop H-infinity performance, sufficient conditions are derived for another controller to be stabilizing and satisfy the same level of H-infinity performance. Such controllers are said to be (P, gamma)-admissible, where P is the model of the plant under consideration and gamma is the required level of prespecified H-infinity, performance. The conditions are expressed as norm bounds on particular frequency-weighted errors, where the weights are Selected to make a specific transfer function a contraction. The design of reduced-order (P,gamma)-admissible controllers is then formulated as a frequency-weighted model reduction problem. It is advantageous for the required weights to be large in some sense, Solutions which minimize either the trace, or the determinant, of the inverse weights are characterized. We show that the procedure for minimizing the determinant of the inverse weights always gives a direction where the weights are the best possible. To conclude, we demonstrate by way of a numerical example, that when used in conjunction with a combined model reduction/convex optimization scheme, the proposed design procedures are effective in substantially reducing controller complexity.
Keywords:
controller approximation
frequency-weighted model reduction
H-infinity control
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Automatic Control cover
IEEE Transactions on Automatic Control
IF:
7
Papers:
1.3W
Citations:
6.7W

Organization

No organization information available
Cited Papers

Cited Papers

Hyperspectral Reflectance Proxies to Diagnose In-Field Fusarium Head Blight in Wheat with Machine Learning
err2022-06-10
err0
errOAAI
errGhulam Mustafa; Hengbiao Zheng; Imran Haider Khan; Long Tian; Haiyan Jia; Guoqiang Li; Tao Cheng; Yongchao Tian; Weixing Cao; Yan Zhu; Xia Yao
errShare
errSave
A toolset to study functions of Cytosolic non-specific dipeptidase 2 (CNDP2) using Drosophila as a model organism
err2019-03-18
err0
errOAAI
errEvgeniya N. Andreyeva; Anna A. Ogienko; Tatiana D. Dubatolova; Anastasiya L. Oshchepkova; Elena N. Kozhevnikova; Anton V. Ivankin; Gera A. Pavlova; Sergei A. Kopyl; Alexey V. Pindyurin
errShare
errSave
Selective and effective anticancer agents: Synthesis, biological evaluation and structure–activity relationships of novel carbazole derivatives
err2021-08-01
err0
PREAI
errWenbo Huang; Zilin Gao; Zhigang Zhang; Wei Fang; Zuoqian Wang; Zhongyi Wan; Liqiao Shi; Kaimei Wang; Shaoyong Ke
errShare
errSave
errShare
errSave
How does surface wettability influence nucleate boiling?
err2009-05-01
err0
errOAAI
errHai Trieu Phan; Nadia Caney; Philippe Marty; Stéphane Colasson; Jérôme Gavillet
errShare
errSave
researcher View more