2000 Fiscal Year Final Research Report Summary
Realization and Subspace Identification of Continuous-Time Stochastic Systems
| Project/Area Number |
11650446
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Control engineering
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| Research Institution | KYOTO UNIVERSITY |
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Principal Investigator |
KATAYAMA Tohru Kyoto University, School of Informatics, Professor, 情報学研究科, 教授 (40026175)
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| Co-Investigator(Kenkyū-buntansha) |
TANAKA Hideyuki Kyoto University, School of Informatics, Research Associate, 情報学研究科, 助手 (90303883)
TAKABA Kiyotsugu Kyoto University, School of Informatics, Associate Professor, 情報学研究科, 助教授 (30236343)
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| Project Period (FY) |
1999 – 2000
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| Keywords | Stochastic Realization / Subspace Method / δ-Operator Model / Continuous-Time System / QR Decomposition / Closed-Loop Identification |
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| Research Abstract |
In standard system identification, the discrete-time models are commonly employed since the plant input-output data are sampled, stored and processed digitally. For mechanical systems, however, it is necessary to identify mass, spring constant and damping factor in the continuous-time model, since most physical systems are continuous in time. This fact motivates recent development in continuous-time system identification.
1. We derive an approximate δ-operator model and then the δ-operator innovation model for a continuous-time stochastic system. Then, applying the MOESP-type subspace identification method to the innovation model, we have obtained a new subspace identification method for a continuous-time system. Moreover, the instrumental matrix is introduced in order to improve the accuracy of the identified models. Simulation results are included. These results are presented at the 31st ISCIE Stochastic System Symposium (1999) and published in Trans. ISCIE (2001).
2. We applied the above δ-operator based technique to the identification of a continuous-time closed-loop system under the assumption that the controller is known. Based on the dual Youla parametrization, the closed-loop identification problem is transformed to an equivalent open-loop identification for the joint input-output process of the plant. The estimate of the desired open-loop transfer matrix is algebraically derived from the state-space model of the joint process. It should be noted that the present technique can be used for the case where the knowledge of controller is available. Simulation results shows that the present technique is applied to the identification of unstable plant. The result is presented at the 3rd Asian Control Conference (2000).
3. Based on the δ-operator approximation, we have derived a method of model set identification for a continuous-time stochastic system by using the modified ellipsoidal bounding technique. The result is published in Trans. ISCIE (1999).
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