Majorization: a computational complexity reduction technique in control system design
- 1 November 1988
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Automatic Control
- Vol. 33 (11) , 1010-1021
- https://doi.org/10.1109/9.14413
Abstract
A methodology is presented for transcribing worst-case control-system design specifications into semi-infinite inequalities of low computational complexity, which are tractable by semi-infinite programming algorithms. These algorithms can be used to find a design which satisfies specifications or to find a design which satisfies specifications and minimizes a cost. A computational example is given.Keywords
This publication has 16 references indexed in Scilit:
- Adaptive control of ARMA plants using worst-case design by semi-infinite optimizationIEEE Transactions on Automatic Control, 1987
- Internal model control and process uncertainty: mapping uncertainty regions for SISO controller designInternational Journal of Control, 1986
- Use of a Monte Carlo method in an algorithm which solves a set of functional inequalitiesJournal of Optimization Theory and Applications, 1985
- A modified Nyquist stability test for use in computer-aided designIEEE Transactions on Automatic Control, 1984
- Control system design via semi-infinite optimization: A reviewProceedings of the IEEE, 1984
- Nondifferentiable optimization algorithm for designing control systems having singular value inequalitiesAutomatica, 1982
- Multivariable feedback design: Concepts for a classical/modern synthesisIEEE Transactions on Automatic Control, 1981
- An improved algorithm for optimization problems with functional inequality constraintsIEEE Transactions on Automatic Control, 1980
- Frequency-domain design of feedback systems for specified insensitivity of time-domain response to parameter variationInternational Journal of Control, 1977
- Generalized gradients and applicationsTransactions of the American Mathematical Society, 1975