An Adaptive Active Disturbance Rejection Control Strategy for Speed-Sensorless Induction Motor Drives

Zuo, Yun; Ge, Xinglai; Zheng, Yuelei; Chen, Yuexuan; Wang, Huimin; Woldegiorgis, Abebe Teklu

doi:10.1109/tte.2022.3148412

Cited by 33 publications

(8 citation statements)

References 53 publications

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“…The stator currents in the real-time domain will be transformed into space vectors in [α, β] stationary coordinates by Clarke transform. Current and voltage signals using estimation algorithms such as SMO, RFMRAS, CBMRAS, etc., [16][17][18][19][20] will be applied to create an estimated speed to diagnose sensor conditions and replace the measuring speed if a speed sensor fault occurs. The voltage and measured speed signals are used to estimate the virtual current through proper estimation methods.…”

Section: Fault-tolerant Controlmentioning

confidence: 99%

“…When the measured signals are correct, they will be transferred to the FOC loop for speed control. If the sensor fails, faulty measured signals are rejected and replaced with estimated speed [ 16 , 17 , 18 , 19 , 20 ] and virtual currents [ 21 , 22 , 23 , 24 , 25 ]. The total failure states of the sensors are simulated to evaluate the effectiveness of the proposed technique.…”

Section: Introductionmentioning

confidence: 99%

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Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Tran,

Kuchar,

Sotola

et al. 2024

Sensors

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This paper proposes a fault-tolerant control (FTC) strategy using the current space vectors to diagnose sensor failures and enhance the sustained operation of a field-oriented (FO) controlled induction motor drive (IMD). Three space vectors are established for the sensor fault diagnosis technique, including one converted from the measured currents and the other two calculated from the current estimation technique, respectively, measured and with reference speeds. A mixed mathematical model using three space vectors and their components is proposed to accurately determine the fault condition of each sensor in the motor drive. After determining the operating status of each sensor, if the sensor signal is in good condition, the feedback signal to the controller will be the measured signal; otherwise, the estimated signal will be used instead of the failed signal. Failure states of the various sensors were simulated to check the effectiveness of the proposed technique in the Matlab/Simulink environment. The simulation results are positive: the IMD system applying the proposed FTC technique accurately detected the failed sensor and maintained stability during the operation.

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Section: Fault-tolerant Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Tran,

Kuchar,

Sotola

et al. 2024

Sensors

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“…There have been several approaches to improving the control of Ims, including model-based predictive control (MPC), field-oriented control (FOC), and direct torque control (DTC). There have been numerous reports that have combined the benefits of IM drives with sensorless control techniques to create low-cost, high-performance actuators [ 12 , 13 ]. In the literature, there have been a variety of approaches proposed for sensorless control of IM drives, but many challenges and uncertainties remain.…”

Section: Introductionmentioning

confidence: 99%

Digital Twin Model of Electric Drives Empowered by EKF

Ebadpour

Jamshidi

Talla

et al. 2023

Sensors

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Digital twins, a product of new-generation information technology development, allows the physical world to be transformed into a virtual digital space and provide technical support for creating a Metaverse. A key factor in the success of Industry 4.0, the fourth industrial revolution, is the integration of cyber–physical systems into machinery to enable connectivity. The digital twin is a promising solution for addressing the challenges of digitally implementing models and smart manufacturing, as it has been successfully applied for many different infrastructures. Using a digital twin for future electric drive applications can help analyze the interaction and effects between the fast-switching inverter and the electric machine, as well as the system’s overall behavior. In this respect, this paper proposes using an Extended Kalman Filter (EKF) digital twin model to accurately estimate the states of a speed sensorless rotor field-oriented controlled induction motor (IM) drive. The accuracy of the state estimation using the EKF depends heavily on the input voltages, which are typically supplied by the inverter. In contrast to previous research that used a low-precision ideal inverter model, this study employs a high-performance EKF observer based on a practical model of the inverter that takes into account the dead-time effects and voltage drops of switching devices. To demonstrate the effectiveness of the EKF digital twinning on the IM drive system, simulations were run using the MATLAB/Simulink software (R2022a), and results are compared with a set of actual data coming from a 4 kW three-phase IM as a physical entity.

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“…However, these sensors not only add to the cost but also complicate the system by introducing additional components that require maintenance and are prone to failure. Consequently, research is veering towards sensorless control techniques that can effectively estimate motor speed without needing dedicated speed sensors, thereby reducing the cost and complexity of the control process [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Speed Control of Induction Motor Using Model Reference Adaptive System and Deadbeat Regulator

Hamdi,

Hammoudi,

Betka

2023

Asec 2023

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An Adaptive Active Disturbance Rejection Control Strategy for Speed-Sensorless Induction Motor Drives

Cited by 33 publications

References 53 publications

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Digital Twin Model of Electric Drives Empowered by EKF

Sensorless Speed Control of Induction Motor Using Model Reference Adaptive System and Deadbeat Regulator

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