Robust control under parametric uncertainty via primal-dual convex analysis

A numerical method is proposed for optimal robust control synthesis. The method applies to the case when the coefficients of the characteristic polynomial depend linearly on the uncertain parameters. A primal/dual pair of infinite-dimensional convex problems is solved by successive finite-dimensiona...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2002-04, Vol.47 (4), p.632-636
Main Authors: Ghulchak, A., Rantzer, A.
Format: Article
Language:English
Subjects:
Applied sciences
Approximation
Automatic control
Computer science
control theory
systems
Control Engineering
Control system synthesis
Control systems
Control theory. Systems
Convex optimization
Design methodology
duality
Electrical Engineering, Electronic Engineering, Information Engineering
Elektroteknik och elektronik
Engineering and Technology
Exact sciences and technology
finite-approximation
Frequency response
Linear systems
Lower bounds
Mathematical models
Optimal control
Optimization
parametric uncertainty
Polynomials
Reglerteknik
Robust control
Robust stability
robust stabilization
Robustness
Synthesis
Teknik
Uncertainty
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Summary:A numerical method is proposed for optimal robust control synthesis. The method applies to the case when the coefficients of the characteristic polynomial depend linearly on the uncertain parameters. A primal/dual pair of infinite-dimensional convex problems is solved by successive finite-dimensional approximations. The primal/dual pair has no duality gap, and both upper and lower bounds produced by the approximations converge monotonically to the optimal value.
ISSN:0018-9286
1558-2523
DOI:10.1109/9.995040