On avoiding vertexization of robustness problems: The approximate feasibility concept

IEEE Transactions on Automatic Control

Volumn 47, Issue 5, 2002, Pages 819-824

  Barmish, B Ross ^a   Shcherbakov, Pavel S ^b  

^a Case Western Reserve University   (United States)

^b TRAPEZNIKOV INSTITUTE OF CONTROL SCIENCES   (Russian Federation)

Author keywords

Computational complexity; Convex optimization; Monte Carlo methods; Robustness analysis and design

Indexed keywords

APPROXIMATION THEORY; COMBINATORIAL MATHEMATICS; COMPUTATIONAL COMPLEXITY; MONTE CARLO METHODS; PARAMETER ESTIMATION; PROBLEM SOLVING; VECTORS;

VERTEXIZATION;

ROBUSTNESS (CONTROL SYSTEMS);

EID: 0036576781     PISSN: 00189286     EISSN: None     Source Type: Journal    
DOI: 10.1109/TAC.2002.1000280     Document Type: Article

References (12)

1. A survey of computational complexity results in systems and control
2. Linear matrix inequalities with uncertain parameters: The approximate feasibility concept
3. Relaxations of parameterized LMIs with control applications
4. Robust solutions to least-squares problems with uncertain data
5. On avoiding vertexization of robustness problems: The approximate feasibility concept
6. Stochastic robustness of linear time-invariant control systems
7. Probabilistic robustness analysis: Explicit bounds for the minimum number of samples
8. Probabilistic search algorithms for robust stability analysis and their complexity properties