Artificial neural network-based current control of field oriented controlled induction motor drive
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ORIGINAL PAPER
Artificial neural network-based current control of field oriented controlled induction motor drive Ambrish Devanshu1,2
· Madhusudan Singh1 · Narendra Kumar1
Received: 9 May 2019 / Accepted: 22 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract A hysteresis current controller (HCC) is commonly used in high-performance AC motor drives to control the current directly. Recently, the predictive current controller (PCC) is also used as an alternative to the classical current controller for speed and torque regulation of induction motor (IM) drives. However, PCC has drawbacks of large flux and torque ripples, large total harmonic distortions (THDs) in current and voltage and dependency on parameters. This paper proposes current control with artificial neural network (ANN) for a field-oriented controlled induction motor (FOCIM) drive. The ANN has input current error between the reference and the measured stator currents. The output function of neuron is a hyperbolic tan (or tan-sigmoid) function to apply error Levenberg–Marquardt (L–M) back propagation as learning rule because of its fast convergence. The proposed method is based on a new approach in which hysteresis band is replaced by ANN comparator to improve the performance of the FOCIM drive. It minimizes torque ripples, flux ripples, voltage and current THDs over the existing HCC and PCC methods. The superiority of the proposed method compared to existing methods is established by simulation and experimental results. Keywords Induction motor · Field oriented control · Predictive current control · Artificial neural network · Hysteresis current control
1 Introduction The power electronic converters are key elements for the operation of AC drives, utilization of renewable energy and many other commercial and industrial systems. With the rise in energy demands, efficiency and power quality issues in electrical energy conversion, use of semiconductor switches has become a very important area of research during past few decades. In order to fulfil these requirements, new control techniques, topologies and new semiconductor switches are being developed. Many switching control methods such as hysteresis current control, linear control with pulse width modulation (PWM), sliding mode control, predictive current control (PCC) and current control using artificial intelligence techniques are proposed for operation and control of
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Ambrish Devanshu [email protected]
1
Electrical Engineering Department, Delhi Technological University, Delhi, India
2
Electrical Engineering Department, Meerut Institute of Engineering and Technology, Meerut, India
power converters and drives [1, 2]. In these control methods, hysteresis control and linear control with PWM are well established methods in the literature. The HCC keeps the current within the hysteresis band by altering the switching state of the inverter every time current touches the boundary. This technique is theoretically and practically easy to implement as its imple
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