An Adaptive Speed Observer based on a New Total Least-Squares Neuron for Induction Machine Drives

This paper proposes a new observer which computes the rotor speed of an induction motor by employing on-line a least-square algorithm implemented by an original neuron (TLS EXIN). It minimises the estimation error from the equation of the Luenberger observer considering the rotor flux-linkage estimation uncertainty. Experimental results show the goodness of this algorithm which outcomes the Matsuse observer in speed estimation accuracy at very low speed and zero-speed operation at no-load and at load. Moreover it has been verified both numerically and experimentally that this observer works properly even at very low speeds in regenerating mode without any instability.