“…The simulated induction motor is φ 3 , 220 V, 1 hp. The model parameters for this motor are [7] Figures 4 and 5 show the estimated α -axis rotor flux by the algorithm in [7] and the proposed methods respectively. The proposed technique is effective to reduce the phase difference.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Then it is necessary to remove the dc components of the signals both before and after they are integrated. An adaptive filter (ADALINE) as presented in [7] used as a notch filter to cut off the dc component adaptively. Fig.2 shows the adaptive integrator with two identical neural notch filters before and after the pure integrator [7].…”
Section: Rotor Flux Estimationmentioning
confidence: 99%
“…The learning law of the neural adaptive filter is based on the algorithm suggested in [7], the fluxlinkage λ is obtained from back e.m.f by an integration method accomplished by programmable cascaded low-pass filter (PCLPF) implement by a hybrid neural network consisting of a recurrent neural network (RNN) and a feedforward artificial neural network (FFANN).…”
Section: Fig 3 Block Diagram Of the Integration Algorithmmentioning
confidence: 99%
“…The current model is highly sensitive to motor parameters. On the other hand, integration or low pass filter-based flux estimators introduce error due to dc offset value [6] & [7]. To solve the problem notch filter is introduced in [6].…”
Section: Introductionmentioning
confidence: 99%
“…To solve the problem notch filter is introduced in [6]. The same methodology is applied through adaptive integration ANN estimators are given in [7]. This method is highly speed and back emf sensitive and needs some modifications.…”
“…The simulated induction motor is φ 3 , 220 V, 1 hp. The model parameters for this motor are [7] Figures 4 and 5 show the estimated α -axis rotor flux by the algorithm in [7] and the proposed methods respectively. The proposed technique is effective to reduce the phase difference.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Then it is necessary to remove the dc components of the signals both before and after they are integrated. An adaptive filter (ADALINE) as presented in [7] used as a notch filter to cut off the dc component adaptively. Fig.2 shows the adaptive integrator with two identical neural notch filters before and after the pure integrator [7].…”
Section: Rotor Flux Estimationmentioning
confidence: 99%
“…The learning law of the neural adaptive filter is based on the algorithm suggested in [7], the fluxlinkage λ is obtained from back e.m.f by an integration method accomplished by programmable cascaded low-pass filter (PCLPF) implement by a hybrid neural network consisting of a recurrent neural network (RNN) and a feedforward artificial neural network (FFANN).…”
Section: Fig 3 Block Diagram Of the Integration Algorithmmentioning
confidence: 99%
“…The current model is highly sensitive to motor parameters. On the other hand, integration or low pass filter-based flux estimators introduce error due to dc offset value [6] & [7]. To solve the problem notch filter is introduced in [6].…”
Section: Introductionmentioning
confidence: 99%
“…To solve the problem notch filter is introduced in [6]. The same methodology is applied through adaptive integration ANN estimators are given in [7]. This method is highly speed and back emf sensitive and needs some modifications.…”
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