Title :
On stochastic balancing related model reduction
Author_Institution :
Inst. of Robotics & Mechatronics., German Aerosp. Res. Establ., Oberpfaffenhofen, Germany
Abstract :
We propose a general method based on the balanced stochastic truncation (BST) approach for the model reduction of stable linear systems. The new method relies on a recent general inner-outer factorization result and extends the applicability of the BST method to systems with infinite zeros. A computational algorithm with enhanced accuracy for the new BST model reduction approach is presented. The capabilities and advantages of the new approach are illustrated on an example
Keywords :
control system analysis computing; controllability; discrete time systems; linear systems; poles and zeros; reduced order systems; state-space methods; transfer function matrices; Riccati equation; balanced stochastic truncation; controllability; discrete time systems; infinite zeros; inner-outer factorization; linear systems; model reduction; state space; transfer function matrix; Binary search trees; Controllability; Linear systems; Mechatronics; Reduced order systems; Riccati equations; Robots; State-space methods; Stochastic processes; Stochastic systems;
Conference_Titel :
Decision and Control, 2000. Proceedings of the 39th IEEE Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6638-7
DOI :
10.1109/CDC.2000.914156
