Title :
Balanced truncation model reduction of periodic systems
Author_Institution :
Inst. of Robotics & Mechatronics, German Aerosp. Res. Establ., Oberpfaffenhofen, Germany
Abstract :
The balanced truncation approach to model reduction is considered for linear discrete-time periodic systems with time-varying dimensions. Stability of the reduced model is proved and a guaranteed additive bound is derived for the approximation error. These results represent generalizations of the corresponding ones for standard discrete-time systems. Two numerically reliable methods to compute reduced order models using the balanced truncation approach are considered. The square-root method and the potentially more accurate balancing-free square-root method belong to the family of methods with guaranteed enhanced computational accuracy. The key numerical computation in both methods is the determination of the Cholesky factors of the periodic Grammian matrices by solving nonnegative periodic Lyapunov equations with time-varying dimensions directly for the Cholesky factors of the solutions
Keywords :
discrete time systems; linear systems; matrix algebra; reduced order systems; time-varying systems; Cholesky factors; approximation error; balanced truncation model reduction; balancing-free square-root method; computational accuracy; guaranteed additive bound; linear discrete-time periodic systems; nonnegative periodic Lyapunov equations; periodic Grammian matrices; reduced order models; time-varying dimensions; Approximation error; Equations; Linear matrix inequalities; Mechatronics; Observability; Reduced order systems; Robots; Stability; Time varying 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.2000.914155