Statistical approach to Control Performance Assessment (CPA) is of great practical importance. This is particularly visible in process industry, where there are many PID loops. They are often assessed with measures derived from the Gaussian probabilistic density function. Standard deviation, variance, skewness or kurtosis form the majority of applied indexes. The review of data originating from process industry shows, however, to the contrary, that these signals have rather non-Gaussian properties and are mostly characterized by fat-tailed distribution disable the ability. Investigations show that strong disturbances may significantly disable the capacity of proper assessment. Standard measures often fail in such cases. It is shown that non-Gaussian measures can help with this problem. Various disturbances are tested and compared. Results show that fat-tailed distributions are an interesting alternative. They are less sensitive to disturbance shadowing and still make possible loop dynamic assessment.
Przedstawiono nowe miary statystyczne służące do porównywania dokładności modeli propagacyjnych, co umożliwia wybór optymalnego modelu i jego parametrów. Korzystając z tradycyjnych i nowych miar statystycznych dokonano porównania kilku modeli propagacyjnych dla radiofonii UKF-FM na podstawie wykonanych pomiarów propagacyjnych w Warszawie i okolicach.
EN
The paper presents the new statistical measures for comparison of the propagation model accuracy, which can help to choose the optimal model and its parameters. Using the traditional and the new statistical measures and the results of the propagation measurements in Warsaw and the region of Warsaw, the comparison of a few UHF propagation models for FM radio has been done.
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