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Sensorless vector and direct torque control

Peter Vas
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TLDR
This paper presents a space-phasor model of A.C. machines based on artificial intelligence-based steady-state and transient analysis of electrical machines, estimators and investigates the role of magnetic saturation in the control of these machines.
Abstract
1. Introduction 2. The space-phasor model of A.C. machines 3. Vector and direct torque control of synchronous machines 4. Vector and direct torque control of induction machines 5. Torque control of switched reluctance motors 6. Effects of magnetic saturation 7. Artificial intelligence-based steady-state and transient analysis of electrical machines, estimators 8. Self-commissioning Index

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A Review on Position/Speed Sensorless Control for Permanent-Magnet Synchronous Machine-Based Wind Energy Conversion Systems

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Feedforward Neural Network Implementation in FPGA Using Layer Multiplexing for Effective Resource Utilization

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Inverter nonlinearity effects in high frequency signal injection-based, sensorless control methods

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Neural MPPT Control of Wind Generators With Induction Machines Without Speed Sensors

TL;DR: A GNG network has been trained offline to learn the turbine-characteristic surface torque versus wind and machine speeds and has been implemented online to obtain the wind tangential speed on the basis of the estimated torque and measured machine speed (surface function inversion).