Title
Design Of Sampled-Data Systems With Large Plant Uncertainty Using Quantitative Feedback Theory
Abstract
This paper proposes a new quantitative feedback theory (QFT) design framework for dealing,with sampled-data systems with large plant uncertainty. After the QFT-based design in the continuous-time domain is completed, the analogue controller can he transformed directly into a rational discrete-time transfer function via approximate Z transform with the sampling time as a free parameter. The sampling time can therefore be adjusted to make the uncertain sampled-data system robustly stable. In comparison with other approaches, our approach is much more systematic without the solvability problem and yet significant enough to guide the designer to realize the physical controller in which the plant transfer function has prescribed bounds on its parameters. Several examples are used to illustrate the proposed approach and excellent results are obtained.
Year
DOI
Venue
2001
10.1080/002077201300029548
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Keywords
Field
DocType
discrete time,electrical engineering,transfer function,quantitative feedback theory
Z-transform,Control theory,Mathematical optimization,Design framework,Quantitative feedback theory,Control theory,Sampling time,Transfer function,Sampled data systems,Mathematics,Free parameter
Journal
Volume
Issue
ISSN
32
3
0020-7721
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Tsung-Chih Lin136126.73
cash wang200.34
Ching-Cheng Teng347231.50
Tsu-Tian Lee41635148.07