Journal ArticleDOI
Speed-Sensorless Vector Control of a Bearingless Induction Motor With Artificial Neural Network Inverse Speed Observer
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TLDR
In this article, a speed observation scheme using artificial neural network (ANN) inverse method was proposed to effectively reject the influence of speed detection on system stability and precision for a bearingless induction motor.Abstract:
To effectively reject the influence of speed detection on system stability and precision for a bearingless induction motor, this paper proposes a novel speed observation scheme using artificial neural network (ANN) inverse method. The inherent subsystem consisting of speed and torque winding currents is modeled, and then its inversion is implemented by the ANN. The speed is successfully observed via cascading the original subsystem with its inversion. The observed speed is fed back in the speed control loop, and thus, the speed-sensorless vector drive is realized. The effectiveness of this proposed strategy has been demonstrated by experimental results.read more
Citations
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High-Performance Control for a Bearingless Permanent-Magnet Synchronous Motor Using Neural Network Inverse Scheme Plus Internal Model Controllers
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Core Losses Analysis of a Novel 16/10 Segmented Rotor Switched Reluctance BSG Motor for HEVs Using Nonlinear Lumped Parameter Equivalent Circuit Model
TL;DR: Experimental results show that the proposed model can significantly improve the calculation accuracy of core losses of the SSRM, and the accuracy is better than the conventional Epstein frame method.
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Precise control of a four degree-of-freedom permanent magnet biased active magnetic bearing system in a magnetically suspended direct-driven spindle using neural network inverse scheme
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Intelligent computing for numerical treatment of nonlinear prey–predator models
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Journal ArticleDOI
MPTC for PMSMs of EVs With Multi-Motor Driven System Considering Optimal Energy Allocation
Xiaodong Sun,Hu Changchang,Jianguo Zhu,Shaohua Wang,Zhou Weiqi,Zebin Yang,Gang Lei,Ke Li,Bin Zhu,Youguang Guo +9 more
TL;DR: The model predictive torque control (MPTC) method is employed for high-speed and in-wheel motor drives to improve the performance of motor controllers and Experimental comparison with field-oriented control (FOC) shows the advantages of MPTC in dynamic response.
References
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Journal ArticleDOI
Stator-Current-Based MRAS Estimator for a Wide Range Speed-Sensorless Induction-Motor Drive
TL;DR: The allowable range of motor-parameter changes is determined, which guarantees the stable operation of the sensorless field-oriented IM drive with this speed and flux estimator, and the stability of the whole drive system is guaranteed.
Journal ArticleDOI
Speed-Sensorless Estimation for Induction Motors Using Extended Kalman Filters
TL;DR: Extended-Kalman-filter-based estimation algorithms that could be used in combination with the speed-sensorless field-oriented control and direct-torque control of induction motors (IMs) are developed and implemented experimentally and motivated by the lost coupling effect at very low and zero speed.
Journal ArticleDOI
MRAS Sensorless Vector Control of an Induction Motor Using New Sliding-Mode and Fuzzy-Logic Adaptation Mechanisms
TL;DR: A new speed-estimation adaptation law is derived using Lyapunov theory to ensure estimation stability, as well as fast error dynamics in both modes of operations.
Journal ArticleDOI
Direct Torque and Indirect Flux Control of Brushless DC Motor
TL;DR: In this paper, a sensorless three-phase conduction direct torque control (DTC) for brushless dc motors with nonsinusoidal back electromotive force (EMF) has been investigated.
Journal ArticleDOI
Robust backstepping control of induction motors using neural networks
Chiman Kwan,Frank L. Lewis +1 more
TL;DR: A new robust control technique for induction motors using neural networks (NNs) which is systematic and robust to parameter variations and does not require regression matrices, so that no preliminary dynamical analysis is needed.