Transformation of Uncertain Linear Systems with Real Eigenvalues into Cooperative Form: The Case of Constant and Time-Varying Bounded Parameters

Continuous-time linear systems with uncertain parameters are widely used for modeling real-life processes. The parameters, contained in the system and input matrices, can be constant or time-varying. In latter case, they may represent state dependencies of these matrices. Assuming bounded uncertainties, interval methods become applicable a verified reachability analysis, feasibility analysis feedback controllers, design robust set-valued estimators. evaluation models becomes computationally efficient after transformation into cooperative state-space representation, where dynamics satisfy certain monotonicity properties respect to initial conditions. To obtain such representations, similarity transformations required which not trivial find sufficiently wide a-priori bounds parameters. This paper deals derivation algorithmic comparison two different techniques their applicability processes time-varying has distinguished. An interval-based states simple electric step-down converter concludes this paper.