PUMA publications for /tag/optimization%20programsTue Dec 07 20:40:52 CET 2021Int. J. Control5851-864{R}obust $l_1$ performance analysis for linear systems with parametric uncertainties812008EXC310 approach dependent functions imng inequality lyapunov matrix optimization peerReviewed pn4 programs relaxations In this contribution, a computational approach for analysing the robust e.-gain (or the robust l(1) performance) of uncertain linear systems is developed. In particular, the system's state-space matrices may have a rational dependence on structured parametric time-invariant or time-varying uncertainties. The computation is based on robust semi-definite programming and provides a trade-off between accuracy and computational effort. A novel matrix inequality condition to determine the star-norm of discrete-time systems is derived as an auxiliary result.Wed Dec 01 20:49:49 CET 2021Int. J. Controlmay5851-864{R}obust $l_1$ performance analysis for linear systems with parametric uncertainties812008approach lyapunov functions relaxations imng matrix inequality from:carsten.scherer EXC310 optimization pn4 peerReviewed programs dependent In this contribution, a computational approach for analysing the robust e.-gain (or the robust l(1) performance) of uncertain linear systems is developed. In particular, the system's state-space matrices may have a rational dependence on structured parametric time-invariant or time-varying uncertainties. The computation is based on robust semi-definite programming and provides a trade-off between accuracy and computational effort. A novel matrix inequality condition to determine the star-norm of discrete-time systems is derived as an auxiliary result.optimization programsCommunity for tag(s) optimization programs