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The problem of making the Kalman filter robust is considered in the paper. Proceeding from the equivalence between the Kalman filter and the least squares regression problem, a statistical approach named M -estimation is suggested to resolve the regression problem robustly. Since the derived robust M -filters do not have an attractive recursive form, the possibility is proposed of designing real-time estimators based on the general formulation of the robust stochastic approximation algorithm and step-by-step optimization with respect to the weighting matrix combined with suitable approximations. Results of simulation demonstrating the robustness of the proposed estimators are also included.

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The fuzzy logic approach to the automatic classification of moving target detected by ground surveillance radar is presented in this paper. The real audio Doppler signatures of various targets are analyzed by spectrogram. As a result of analysis, input and output variables with corresponding membership function are defined. The set of fuzzy rules is established. The defuzzification of the output fuzzy set is performed by computing the "fuzzy centroid". The three target classes (walking man, running man and wheeled vehicle) are successfully classified.

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An innovative approach to condition-based maintenance of coal grinding subsystems at thermoelectric power plants is proposed in the paper. Coal mill grinding tables become worn over time and need to be replaced through time-based maintenance, after a certain number of service hours. At times such replacement is necessary earlier or later than prescribed, depending on the quality of the coal and of the grinding table itself. Considerable financial losses are incurred when the entire coal grinding subsystem is shut down and the grinding table found to not actually require replacement. The only way to determine whether replacement is necessary is to shut down and open the entire subsystem for visual inspection. The proposed algorithm supports condition-based maintenance and involves the application ofT2control charts to distinct acoustic signal parameters in the frequency domain and the construction of Hidden Markov Models whose observations are coded samples from the control charts. In the present research, the acoustic signals were collected by coal mill monitoring at the thermoelectric power plant “Kostolac” in Serbia. The proposed approach provides information about the current condition of the grinding table.

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