Title :
Longwall mining automation an application of minimum-variance smoothing [Applications of Control]
Author :
Einicke, Garry ; Ralston, J. ; Hargrave, Chad ; Reid, Dave ; Hainsworth, D.
Author_Institution :
CSIRO, Pullenvale, QLD
Abstract :
This article reviews the development of the minimum-variance smoother and describes its use in longwall automation. We describe both continuous- and discrete-time smoother solutions. It is shown, under suitable assumptions, that the two-norm of the smoother estimation error is less than that for the Kalman filter. A simulation study is presented to compare the performance of the minimum-variance smoother with the methods of H.E. Rauch et al. (1965), and D.C. Fraser and J.E. Potter (1969).
Keywords :
Kalman filters; continuous time systems; discrete time systems; mining industry; smoothing methods; Kalman filter; continuous-time smoother solution; discrete-time smoother solutions; longwall mining automation; minimum-variance smoothing; smoother estimation error; Automatic control; Automation; Control systems; Estimation error; Filters; Gaussian noise; Mining equipment; Smoothing methods; State estimation; Technological innovation;
Journal_Title :
Control Systems, IEEE
DOI :
10.1109/MCS.2008.929281
