Sensorless and Adaptive Control of Induction Machines

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: closed (30 June 2025) | Viewed by 1737

Special Issue Editor


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Guest Editor
Department of Industrial Electrical Power Conversion, University of Malta, MSD2050 Msida, Malta
Interests: sensorless control; electric drives; induction motor; permanent magnet synchronous motor

Special Issue Information

Dear Colleagues,

Induction machines have been widely utilized in industries for decades due to their easy and robust construction as well as their cost-effectiveness. Their simplicity and affordability make them a preferred choice in numerous applications. Achieving dynamic variable speed control of induction motors is made possible through inverter-driven vector control. However, this approach necessitates knowledge of the rotor position, typically obtained by using sensors. Unfortunately, these sensors are rather expensive and delicate electronic devices.

A more resilient alternative is utilizing the induction machine itself as a rotor position sensor, an idea known as "sensorless control." Numerous methods have been proposed and demonstrated promising practical results. In the case of medium- to high-speed applications, many of these sensorless position estimation techniques have been implemented in commercial variable speed drives. However, achieving sensorless control of induction motors in the very low- and zero-speed regions remains a significant research challenge.

Several sensorless techniques employ model-based observers, which are highly sensitive to parameter deviations. Adaptive parameter estimation techniques prove to be immensely helpful in maintaining observer parameters as precise as possible across all motor operation conditions. Other sensorless techniques utilize high-frequency or transient pulse signal responses to estimate magnetic saliencies in the machine rotor. The obtained saliency is typically influenced by the rotor bar slots of the induction rotor cage and modulation due to saturation caused by the motor currents. This requires sophisticated modulation signal separation. Additionally, non-linearities in the machine signals present further challenges.

This Special Issue aims to gather new research results in the domain of sensorless and adaptive control of induction motors.

Research topics that are of interest for this Special Issue include but not limited to the following:

  • Signal injection methods to detect induction motor magnetic saliencies;
  • Model-based sensorless position estimation based on machine flux/back EMF;
  • Hybrid sensorless techniques using back EMF models and magnetic saliency detection;
  • Adaptive parameter estimation of induction machines;
  • Non-linear parameter modelling of induction machines;
  • Pattern recognition of saliency modulation;
  • rotor position reconstruction from measured saliencies;
  • Filtering and signal processing of estimates position signals.

Dr. Reiko Raute
Guest Editor

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Keywords

  • induction motor
  • variable speed drives
  • inverters
  • sensorless control
  • adaptive control
  • parameter estimation

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Published Papers (1 paper)

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Research

16 pages, 1766 KB  
Article
Sensorless Speed Controller for the Induction Motor Using State Feedback and Robust Differentiators
by Onofre Morfin, Fernando Ornelas-Tellez, Nahitt Padilla, Maribel Gomez, Oscar Hernandez, Reymundo Ramirez-Betancour and Fredy Valenzuela
Machines 2025, 13(9), 846; https://doi.org/10.3390/machines13090846 - 12 Sep 2025
Abstract
This paper introduces a novel sensorless speed control strategy for squirrel-cage induction motors, which ensures robust operation in the presence of external disturbances by applying the state feedback technique. Based on the induction motor model, the speed controller is synthesized by defining a [...] Read more.
This paper introduces a novel sensorless speed control strategy for squirrel-cage induction motors, which ensures robust operation in the presence of external disturbances by applying the state feedback technique. Based on the induction motor model, the speed controller is synthesized by defining a sliding variable that is driven to zero through the supertwisting control law, ensuring the stabilization of the tracking error. The time derivative of the error variable is estimated using a robust differentiator based on the sliding-mode twisting algorithm, thereby eliminating the need to estimate the load torque. A robust observer is employed to estimate the rotor speed and flux linkages simultaneously. The convergence of the estimated rotor flux linkages is enforced through a discontinuous first-order sliding-mode input, while the convergence of the rotor speed estimate is attained via a quasi-continuous super-twisting sliding-mode input. In the proposed model, the inductance parameters are determined from the magnetizing inductance and the leakage inductances of the stator and rotor. A procedure is also presented for adjusting the stator resistance and leakage inductances, taking into account the squirrel-cage rotor type and the skin effect in alternating current conduction. The performance of the sensorless speed control system under variations in load torque and reference speed is validated through experimental testing. The rotor speed estimation provided by the robust observer is accurate. The reference speed tracking control, evaluated using a 1600–1700 rpm pulse train phase-shifted by 4 s with respect to a 0–0.5 N·m pulse train, demonstrates high precision. Full article
(This article belongs to the Special Issue Sensorless and Adaptive Control of Induction Machines)
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