Model order reduction for delay systems by iterative interpolation
Dominik Alfke, Lihong Feng, Luigi Lombardi, Giulio Antonini, Peter Benner
Abstract
Abstract Adaptive algorithms for computing the reduced‐order model of time‐delay systems (TDSs) are proposed in this work. The algorithms are based on interpolating the transfer function at multiple expansion points and greedy iterations for selecting the expansion points. The ‐error of the reduced transfer function is used as the criterion for choosing the next new expansion point. One heuristic greedy algorithm and one algorithm based on the error system and adaptive sub‐interval selection are developed. Results on four TDSs with tens of delays from electromagnetic applications are presented and show the efficiency of the proposed algorithms.
Topics & Concepts
Interpolation (computer graphics)Reduction (mathematics)AlgorithmMathematical optimizationTransfer functionGreedy algorithmComputer scienceGreedy randomized adaptive search procedureModel order reductionFunction (biology)HeuristicPoint (geometry)Selection (genetic algorithm)MathematicsEngineeringArtificial intelligenceProjection (relational algebra)Electrical engineeringGeometryMotion (physics)BiologyEvolutionary biologyModel Reduction and Neural NetworksElectromagnetic Simulation and Numerical MethodsNumerical methods for differential equations