Polynomial predictive filtering in control instrumentation: a review

Additional delay is an unavoidable drawback of conventional filters used frequently in industrial electronics. This delay is particularly harmful if the filtered primary signal is to be used for time-critical feedback or synchronization purposes. Therefore, predictive signal processing methods can offer significant advantages for these real-time applications. Polynomial predictive filters are specified without explicit passbands and stopbands, and they are behaving delaylessly or predictively for smoothly varying signal components. The degree of smoothness of the incoming signal sets the requirements for the applied filtering scheme and its parameters. Smoothness of a signal is a fuzzy and application-specific concept: the degree of smoothness depends on the ratio of the bandwidth of the primary signal and the applied sampling rate, as well as the noise component. In this paper, the authors review the most important polynomial predictive filtering methods and algorithms, their design and implementation techniques, and a collection of successful applications.

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