Published in IEEE Control Systems Magazine, Dec 2008 Page 1 of 23 Longwall Mining Automation An application of minimum-variance smoothing Garry Einicke, Jonathon Ralston, Chad Hargrave, David Reid, and David Hainsworth Longwall mining is a method for extracting coal from underground mines. The mining technology involves a longwall shearer, which is a 15-m long, 100-ton machine that has picks attached to two drums, which rotate at 30 to 40 revolutions per minute. A longwall face is the mined area from which material is extracted. The shearer removes coal by traversing a face at approximately 25-minute intervals. Traditionally, longwall mining equipment is controlled manually, where the face is aligned using a string line. Under manual control, the face meanders and wanders out of the coal seam, which causes rock to contaminate the coal and limits the rate of production. Coal production is maximized by maintaining a straight shearer trajectory and keeping the face within the seam. Therefore, precise estimates of the face locations are required so that the longwall equipment can be repositioned after each shear. We are automating longwall equipment to improve production. A Northrop Grumman LN270 inertial navigation unit and an IEEE 802.11b wireless local area network client device are installed within a flame-proof enclosure, which, together with an odometer, are mounted on a shearer. The inertial navigation unit and odometer measure the shearer’s orientation and distance travelled across the face, respectively. The inertial navigation and odometer measurements are stored locally and subsequently forwarded when the shearer is near an access point of the wireless local area network. Upon completion of each shear, inertial navigation and odometer data are used to estimate the position of the face and control the roof support equipment for the next shear. In particular, minimum-variance fixed-interval smoothing is applied to the inertial and odometer measurements to calculate face positions in three-dimensional space. Filtering refers to the process of estimating the current value of a signal from noisy measurements up to the current time. In fixed-interval smoothing, measurements recorded over an interval are used to estimate past values of a signal. Compared to filtering, smoothing can provide improved estimation accuracy at the cost of twice the computational complexity. Smoothing is applicable wherever measurements are organized in blocks and retrospective data analysis is feasible. In the case of longwall mining, the position estimates and controls are calculated while the shearer is momentarily stationary at the ends of the face. The fixed-interval smoothing techniques in use today are innovations of the 1950s and 1960s [1], [2], [3]. In [1], Wiener factorizes power spectral densities and constructs estimators that minimize the error variance. The Wiener solution is called “physically unrealizable by its very nature” [1] because it requires future data. In fact, the Wiener solution is a fixed-interval smoother, which can be implemented by both forward and backward processes. In practice, smoother realizations involve a forward pass over a