Learning Controllers for Performance Through LMI Regions

An LMI Optimization Approach for Structured Linear Controllers

Abstract— This paper presents a new algorithm for the design of linear controllers with special structural constraints imposed on the control gain matrix. This so called SLC (Structured Linear Control) problem can be formulated with linear matrix inequalities (LMI’s) with a nonconvex equality constraint. This class of problems includes fixed order output feedback control, multi-objective contro...

Combining Learning and Programming for High-Performance Robot Controllers

The implementation of high-performance robot controllers for complex control tasks such as playing autonomous robot soccer is tedious, errorprone, and a never ending programming task. In this paper we propose programmers to write autonomous controllers that optimize and automatically adapt themselves to changing circumstances of task execution using explicit perception, dynamics and action mode...

" LMI approach to mixed performance objective controllers : application to Robust H , Synthesis "

The problem of synthesizing a controller for plants subject to arbitrary, finite energy disturbances and white noise disturbances via Linear Matrix Inequalities (LMIs) is presented. This is achieved by considering white noise disturbances as belonging to a constrained set in 12. In the case of where only white noise hsturbances are present, the procedure reduces to standard 312 synthesis. When ...

Robust pole placement in LMI regions

This paper discusses analysis and synthesis techniques for robust pole placement in LMI regions, a class of convex regions of the complex plane that embraces most practically useful stability regions. The focus is on linear systems with static uncertainty on the state matrix. For this class of uncertain systems, the notion of quadratic stability and the related robustness analysis tests are gen...

Robust Pole Pla ement in LMI Regions