Title :
Regression modelling technique for state model estimation and Kalman filter application
Author :
Eagle, Paul J. ; Tabrizi, Lili H.
Author_Institution :
Detroit Univ., MI, USA
Abstract :
Manufacturing processes in which it is necessary to apply a Kalman filter algorithm to estimate the states associated with the process, because of the dynamic elements in the system that are not measurable, is considered. A method for applying the Kalman filter to processes by using a regression model of the output equation for the system is presented. This dynamical model can be applied to state estimation and filtering techniques for process qualification and other applications. An example is given to illustrate the method
Keywords :
Kalman filters; filtering and prediction theory; production control; state estimation; Kalman filter; dynamical model; production control; regression model; state estimation; Analytical models; Difference equations; Differential equations; Electrical equipment industry; Fault detection; Fault diagnosis; Manufacturing processes; Mechanical engineering; Monitoring; State estimation;
Conference_Titel :
Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
0-87942-597-0
DOI :
10.1109/ICSMC.1990.142207
