제어로봇시스템학회:학술대회논문집
- 2002.10a
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- Pages.52.6-52
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- 2002
System Identification Using Observer Kalman filter Identification
- Ryu, Hee-Seob (IAE) ;
- Yoo, Ho-Jun (Inha Univ.) ;
- Kim, Dae-Woo (Unix Electronics Ltd. Co.)
- Published : 2002.10.01
Abstract
The method of identifying the plant models in this paper is the Observer Kalman filter identification (OKID) method. This method of system identification has several pertinent advantages. First, it assumes that the system in question is a discrete linear time-invariant (LTI) state-space system. Second, it requires only input and output data to formulate the model, no a priori knowledge of the system is needed. Third, the OKID method produces a psudo-Kalman state estimator, which is very useful for control applications. Last, the modal balanced realization of the system model means that tuncation errors will be small. Thus, even in the case of model order error the results of that error will...
Keywords