Longwall mining automation an application of minimum-variance smoothing [Applications of Control]

@article{Einicke2008LongwallMA,
  title={Longwall mining automation an application of minimum-variance smoothing [Applications of Control]},
  author={Garry A. Einicke and Johnathon C. Ralston and Chad O. Hargrave and D. Reid and David W. Hainsworth},
  journal={IEEE Control Systems},
  year={2008},
  volume={28}
}
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). 
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