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The stator flux observer is a key part in the method of Direct Torque Control (DTC). However, the accuracy of the stator flux estimation directly affected the performance of DTC. The traditional induction motor stator flux observation method have been analyzed in This paper. And for the Shortcomings of existing methods, a on-line identification methods based on Radial Basis Function(RBF) have been...
In this paper, a hybrid speed controller based on proportional integral (PI) controller and artificial neural network(ANN) is proposed as a speed controller for an indirect field oriented induction motor vector control system. The new controller has self-learning and self-organization capabilities. Its parameters are adjusted online according to back propagation (BP) algorithm. The weighting coefficients...
The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled...
Fault diagnosis of induction motor is gaining importance in industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. Due to environmental stress and many others reasons different faults occur in induction motor. Many researchers proposed different techniques for fault detection and diagnosis. However, many techniques available presently...
A new algorithm for speed observer based on Model Reference Adaptive System (MRAS) is proposed for high performance induction motor drive. It uses stator current error based MRAS speed observer. The reference model of the stator current error based MRAS is the measured stator current components and the adaptive model is neuro-fuzzy based stator current observer. The adaptive model also needs the use...
Motor systems are highly important and are critical components in industrial processes. Up to 60% of the electricity produced in the U.S. converts into other forms of energy to provide power to equipment through motor [1]. Machinery reliability and performance can be improved with early fault diagnosis and condition monitoring; therefore, the fault diagnosis system for motor has been highlighted for...
This paper presents a new method of on-line estimation for the stator and rotor resistances of the induction motor in the indirect vector controlled drive, using artificial neural networks. The back propagation algorithm is used for training of the neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights...
Due to multivariable, highly nonlinear, strong coupling, time-varying dynamics and unavailability of measurements, induction motor control is still a difficult and complex engineering problem. Vector control has replaced traditional control method using the ratio of voltage and frequency as a constant, which improve greatly dynamic control efficiency of motor. However, under the circumstances of changing...
Electromagnetic aircraft launch system (EMALS) use linear motor to accelerate aircraft to launch speed. This paper presents a new method based on fuzzy-neural of HSLIMEO. It is important to improve efficiency not only saving economic and energy, but also reducing environmental pollution. To optimize efficiency, fuzzy controller combined with field-oriented scheme is proposed to work to optimize flux...
In this paper, a speed estimation and control strategy for induction motor drive based on an indirect field-oriented control is presented. The rotor speed estimator based on a RBF neural network utilizes stator voltage and current measured values to calculate the rotor speed, and the control approach based on a sliding-mode controller with an integral sliding surface is proposed in order to regulate...
On the basis of mathematic model analysis of multi-motor synchronous system, intelligent decoupling technology of multi-variable system is introduced to design neural network controller that is composed of self-turning PID controller based on diagonal recurrent neural network and adaptive neuron decoupling compensator, which make use of serial open loop decoupling strategy of adaptive neuron decoupling...
The motor is the workhorse of industry. The control and identification of induction motor with artificial intelligence is the key point for high performance electrical drives. A novel architecture of nonlinear autoregressive moving average (NARMA) model based on wavelet neural networks (WNN) is presented for enhancing the performance of induction motor. The Akaikepsilas final predication error (AFPE)...
This paper presents a new speed-sensorless vector control drive system for induction motor. In order to produce low harmonics in output voltage and current, reduce the torque fluctuation, and avoid the high voltage jump in switching time, the system utilizes three-level inverter to supply power for the induction motor and a SVPWM scheme with neutral point voltage balance strategy is applied for the...
Maglev train is a new vehicle without support wheel and its movement speed is gained through a special measure equipment. The paper proposes a neural network arithmetic for the maglev train speed estimator which combines characteristics of its traction linear induction motor. The result of a dynamic simulation experiment shows that real speed measure is near to theory calculation. This proves that...
In this paper, an approach to DTC control scheme for induction machine is developed which makes DTC more applicable while it has lower torque ripple, lower flux ripple and almost fixed switching frequency rather than other DTC methods. Comparisons between simulation and practical results confirm that not any noticeable advantage of other developed DTCs is lost while it becomes more applicable. The...
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