ANALYSIS OF ALGORITHMS FOR VELOCITY ESTIMATION FROM DISCRETE POSITION VERSUS TIME DATA

This paper investigates algorithms for constructing velocity approximations from discrete position versus time data. The study is limited to algorithms suitable to provide velocity information in discrete-time feedback control systems such as microprocessor-based systems with a discrete position encoder. Velocity estimators based on lines per period, reciprocal-time, Taylor series expansions, backward difference expansions, and least-square curve fits are presented. Based on computer simulations, comparisons of relative accuracies of the different algorithms are made. The least-squares velocity estimators filtered the effect of imperfect measurements ("noise") best, whereas the Taylor series expansions and backward difference equation estimators respond better to velocity transients.