Convex Matrix Inequalities Versus Linear Matrix Inequalities

被引:21
|
作者
Helton, J. William [1 ]
McCullough, Scott [2 ]
Putinar, Mihai [3 ]
Vinnikov, Victor [4 ]
机构
[1] Univ Calif San Diego, Dept Math, La Jolla, CA 92093 USA
[2] Univ Florida, Dept Math, Gainesville, FL 32611 USA
[3] Univ Calif Santa Barbara, Dept Math, Santa Barbara, CA 93106 USA
[4] Ben Gurion Univ Negev, Dept Math, IL-84105 Beer Sheva, Israel
基金
以色列科学基金会; 美国国家科学基金会;
关键词
Algebraic approaches; convex optimization; linear control systems; linear matrix inequality (LMI); STRICT POSITIVSTELLENSATZ; GLOBAL OPTIMIZATION; POLYNOMIALS;
D O I
10.1109/TAC.2009.2017087
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Most linear control problems lead directly to matrix inequalities (MIs). Many of these are badly behaved but a classical core of problems are expressible as linear matrix inequalities (LMIs). In many engineering systems problems convexity has all of the advantages of a LMI. Since LMIs have a structure which is seemingly much more rigid than convex MIs, there is the hope that a convexity based theory will be less restrictive than LMIs. How much more restrictive are LMIs than convex MIs? There are two fundamentally different classes of linear systems problems: dimension free and dimension dependent. A dimension free MI is a MI where the unknowns are g-tuples of matrices and appear in the formulas in a manner which respects matrix multiplication. Most of the classic MIs of control theory are dimension free. Dimension dependent MIs have unknowns which are tuples of numbers. The two classes behave very differently and this survey describes what is known in each case about the relation between convex MIs and LMIs. The proof techniques involve and necessitate new developments in the field of semialgebraic geometry.
引用
收藏
页码:952 / 964
页数:13
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