Sensorless Control Techniques for Induction Motor Drives

Sensorless control of induction motor drives has emerged as a pivotal technology in the pursuit of highly efficient, compact and cost-effective electric drive systems. By dispensing with mechanical speed or position sensors, control schemes rely solely on electrical measurements—principally stator voltages and currents—to estimate rotor speed, flux and torque. Core methodologies include field-oriented control, which decouples torque and flux vectors for independent regulation, and a variety of observer-based estimators such as Model Reference Adaptive Systems (MRAS), Extended Kalman Filters (EKF) and sliding-mode observers. High-frequency signal injection and artificial intelligence methods also address challenges at very low speeds or in the presence of parameter variations. Advances in real-time computation, robust estimation algorithms and adaptive tuning of observer gains have extended the operational envelope of sensorless drives from industrial machinery to electric vehicles and renewable energy systems. Despite a long-standing focus on high-performance regulation, ongoing efforts tackle remaining issues of parameter drift, low-speed stability and electromagnetic interference, underscoring both the global significance and practical applications of these techniques.

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Research from all publishers

Recent studies have demonstrated enhanced observer structures and adaptive tuning strategies to improve robustness and accuracy across all operating conditions. One line of work employs an Improved Extended Kalman Filter whose process and measurement noise covariances are optimised via a genetic algorithm, yielding superior speed and flux estimates in real-time implementations while reducing computational burden. Another approach investigates a dual-architecture speed observer based on sliding super-twisting and backstepping control, comparing stabilisation functions under nominal, low-speed and regenerative modes; experimental results confirm enhanced transient response and resilience to parameter uncertainty. A further development introduces a nonadaptive full-order observer that eschews integrators in rotor speed reconstruction, instead leveraging algebraic relations and novel stabilisation functions to secure observer stability in both motoring and regenerating conditions, even at near-zero speeds. Collectively, these diverse contributions illustrate a trend towards hybridised estimation schemes that combine the deterministic guarantees of sliding-mode theory with adaptive or optimisation-based tuning to meet the stringent demands of modern electric drive applications.

Sensorless Control Techniques for Induction Motor Drives publication trend

The graph below shows the total number of articles in sensorless control techniques for induction motor drives across all publications each year (not limited to Nature Index journals).

Technical terms

Sensorless control: A method of regulating motor speed or position without physical sensors, using measured electrical signals and estimation algorithms.

Field-oriented control (FOC): A vector control technique that decouples torque and flux in an induction motor to enable independent and precise regulation.

Model Reference Adaptive System (MRAS): An observer structure that adjusts its parameters online by comparing a reference model with an adjustable model to estimate motor variables.

Extended Kalman Filter (EKF): A recursive algorithm that linearises a nonlinear system around the current estimate to provide optimal state estimation under uncertainty.

Sliding-mode observer: A discontinuous control approach that forces estimation errors to slide along a predefined manifold, ensuring robustness against disturbances.

Rotor flux: The magnetic flux produced by currents in the rotor windings, which must be accurately estimated for effective vector control.

References

1. Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques. IEEE Transactions on Industrial Informatics (2020).
2. Real-Time Implementation of Extended Kalman Filter Observer With Improved Speed Estimation for Sensorless Control. IEEE Access (2021).
3. Nonadaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer. IEEE Transactions on Industrial Electronics (2021).