Sensorless Control of Induction Motor Drives by New Linear Neural Techniques

This paper summarizes the research activity of the authors in the field of sensorless control of induction machine drives based on new linear neural techniques. In particular it describes and compares three speed observers: the MCA EXIN + MRAS Observer, the MCA EXIN + Reduced Order Observer and the TLS Full-order Luenberger Adaptive Observer. Common to all of three observers is the on-line estimation of the speed by a new linear neural technique, which solves in a recursive way a Total Least-Squares problem: one of them employs the TLS EXIN neuron and the other two the MCA EXIN + neuron, which is an improvement of the former. The speed observers have been verified in numerical simulations and experimentally on a test setup and have been also compared experimentally with one another.