Title :
State model estimation for Kalman filter applications using regression techniques
Author :
Eagle, Paul J. ; Tabrizi, Lili H.
Author_Institution :
Detroit Univ., MI, USA
Abstract :
The authors consider a method for applying the Kalman filter to processes by the use of a regression model of the output equation for the system. The regression model can provide a satisfactory method for estimating the underlying dynamics in a system. This dynamical model can be applied to state estimation and filtering techniques for process qualification and other applications
Keywords :
Kalman filters; dynamics; filtering and prediction theory; state estimation; Kalman filter; dynamics; filtering techniques; regression model; state estimation; Analytical models; Difference equations; Differential equations; Electrical equipment industry; Fault detection; Fault diagnosis; Mechanical engineering; Monitoring; State estimation; Testing;
Conference_Titel :
Decision and Control, 1990., Proceedings of the 29th IEEE Conference on
Conference_Location :
Honolulu, HI
DOI :
10.1109/CDC.1990.203311
