Name
Abstract | ||
|---|---|---|
Stability is a crucial property in the study of dynamical systems. We focus on the problem of enforcing the stability of a system a posteriori. The system can be a matrix or a polynomial either in continuous-time or in discrete-time. We present an algorithm that constructs a sequence of successive stable iterates that tend to a nearby stable approximation X of a given system A. The stable iterates are obtained by projecting A onto the convex approximations of the set of stable systems. Some possible applications for this method are correcting the error arising from some noise in system identification and a possible solver for bilinear matrix inequalities based on convex approximations. In the case of polynomials, a fair complexity is achieved by finding a closed form solution to first order optimality conditions. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.automatica.2013.01.053 | Automatica |
Keywords | Field | DocType |
Lyapunov stability,Time-invariant systems,Polynomials,Inner convex approximation | Mathematical optimization,Polynomial,Matrix (mathematics),Control theory,Lyapunov stability,Dynamical systems theory,Solver,System identification,Iterated function,Mathematics,Linear matrix inequality | Journal |
Volume | Issue | ISSN |
49 | 5 | 0005-1098 |
Citations | PageRank | References |
5 | 0.69 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francois-Xavier Orbandexivry | 1 | 5 | 0.69 |
| Yurii Nesterov | 2 | 1800 | 168.77 |
| Paul van Dooren | 3 | 649 | 90.48 |