TY - GEN
T1 - Super-optimal model reduction in sense of Hankel-norm
AU - Young, Jieh Shian
AU - Wei, Lin Fang
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2004
Y1 - 2004
N2 - The best approximation in the optimal solution set of the Hankel-norm model reduction problem is studied in this paper since the optimal solutions are not unique for linear multi-input-multi-output systems (matrix-value transfer functions). This kind of model reduction problems will be defined properly and intuitively. The sub-layers of the optimal model errors will be characterized by the appropriate Schmidt pairs. The optimal solution set will also be parametrized in the suitable domain in order to keep the reduced model with the constant order after the optimatizations. The results from this proposed approach show that they are better than those from the other optimal approximate models in sense of the Hankel operator singular values.
AB - The best approximation in the optimal solution set of the Hankel-norm model reduction problem is studied in this paper since the optimal solutions are not unique for linear multi-input-multi-output systems (matrix-value transfer functions). This kind of model reduction problems will be defined properly and intuitively. The sub-layers of the optimal model errors will be characterized by the appropriate Schmidt pairs. The optimal solution set will also be parametrized in the suitable domain in order to keep the reduced model with the constant order after the optimatizations. The results from this proposed approach show that they are better than those from the other optimal approximate models in sense of the Hankel operator singular values.
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M3 - Conference contribution
AN - SCOPUS:2942665788
SN - 0780381939
T3 - Conference Proceeding - IEEE International Conference on Networking, Sensing and Control
SP - 767
EP - 772
BT - Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
T2 - Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
Y2 - 21 March 2004 through 23 March 2004
ER -