Technical Report


Recursive Maximum Likelihood Estimation and Output Error Estimation Techniques From Noise Corrupted Data
 
  Hayrettin Bora Karayaka
Ali Keyhani
 
The Ohio State University
Electrical Engineering Department
Columbus Ohio 43210
Tel: 614-292-4430
Fax: 614-292-7596
Keyhani.1@osu.edu
March, 2000

A methodology to estimate armature circuit and field winding parameters of a synchronoususing the synthetic data obtained by the machine natural abc frame of reference simulation is presented. First, a one-machine infinite bus system including the machine and its excitation system is simulated in abc frame of reference by using parameters provided by the machine manufacturer. A proper data set required for estimation is collected by perturbing the field side of the machine in small amounts. The recursive maximum likelihood (RML) estimation technique is employed for the identification of armature circuit parameters. Subsequently, based on the estimates of armature circuit parameters, the field winding and some damper parameters are estimated using an Output Error Estimation (OEM) technique. For each estimation case, the estimation performance is also validated with noise corrupted measurements.
The study shows that noise corruption problems can be effectively handled with the RML algorithm for estimation of armature circuit parameters.. For lower signal to noise ratio(SNR) values, the RML estimates of mutual inductances and field to stator turns ratio has been estimated. The OEM estimation results reveal that good estimates of the actual parameters can be obtained with proper initialization. It is shown that for large excitation disturbances, the OEM estimation technique can recover the model parameters with unobservable state from noise corrupted data.
 

If your company is a member of the Mechatronic Laboratory, please send the request to receive a copy of any technical report. If you are not a member please send a request to Ali Keyhani, Department of Electrical Engineering, Mechatronics Program at the following address: Ali Keyhani, Ohio State University, Electrical Engineering Department, Mechatronics Systems Laboratory, 2015 Neil Ave., 205 Dereese Lab., Columbus, OH 43210.

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