Solving robust Linear Matrix Inequalities (LMIs) has long been recognized as an important problem in robust control. Although the solution to this problem is well-known for the case of affine dependence on the uncertainty, to the best of our knowledge, results for other types of dependence are limited. In this paper we address the the problem of solving robust LMIs for the case of polynomial dependence on the uncertainty. More precisely, results from numerical integration of polynomial functions are used to develop procedures to minimize the volume of the set of uncertain parameters for which the LMI condition is violated.
|Title of host publication
|Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2007
|46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States
Duration: Dec 12 2007 → Dec 14 2007
|Proceedings of the IEEE Conference on Decision and Control
|46th IEEE Conference on Decision and Control 2007, CDC
|New Orleans, LA
|12/12/07 → 12/14/07
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization