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Robust control of constrained systems via convex optimization
Author(s) -
Sznaier Mario,
Blanchini Franco
Publication year - 1995
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4590050506
Subject(s) - robustness (evolution) , computer science , robust control , convex optimization , mathematical optimization , robust optimization , domain (mathematical analysis) , controller (irrigation) , regular polygon , control theory (sociology) , control (management) , control engineering , control system , mathematics , engineering , mathematical analysis , biochemistry , chemistry , agronomy , geometry , artificial intelligence , biology , electrical engineering , gene
A successful controller design paradigm must take into account both model uncertainty and design specifications. Model uncertainty can be successfully addressed using ℋ ∞ robust control theory. However, this framework cannot directly accommodate the realistic case where in addition to robustness considerations the system is subject to both time‐ and frequency‐domain specifications, such as bounds on the control action. In this paper we propose a design procedure, based upon the use of convex optimization, that takes explicitly into account both time‐ and frequency‐domain specifications. The main result of the paper is a new framework to address problems having both control and output constraints and model uncertainty. Additionally, the paper serves as a brief tutorial on the issues involved in addressing design problems with multiple design specifications via convex optimization.