POLITECHNIKA WARSZAWSKA

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4. ANN based Current Controllers Hysteresis Regulator (a) NN Regulator (b) Fig. 4.11 Simulated waveforms for current regulators (δ= 0.05) I - i α , i β , II - u β , III - u α = f(u β ) , IV -voltage vectors 57
4. ANN based Current Controllers Table 4.3 Comparison of the learning rules learning rules Table 4.2 learning rules PWM pattern δ 0.001 0.01 0.1 ⎯ ⎯ NDP ⎯ ⎯ ⎯ 150 450 PSE 87% 87% 72% 94% 92% NDP - number of data points; NLS - number of learning steps (NLS = 100000); PSE - pattern selection efficiency factor. The Number of Learning Steps (NLS) is assumed constant = hundred thousand. It can be seen that Pattern Selection Efficiency factor Number of correct pattern selection PSE = , Total number of pattern selection which shows how often the NN generates the "correct voltage vector", is better for NN trained according to the rules given by "PWM time pattern" than by the rules given in Table 4.2. However, the learning method according to rules given in Table 4.2 is independent of system parameters and, therefore, is much simpler for implementation. 4.3.2.3. Improved Neural Network Current Regulator The discussion and results presented in the previous Section show that the NN regulator proposed by Harashima has performance similar to that of Delta Regulator (Fig. 4.10b). From the other side it is known that Delta Regulator never selects the zero voltage vectors. This leads to poor quality of the output current generation and creates ±1 transition of the DC voltage. These transitions (corresponds to the switching between not adjacent vectors i.e. V 1 →V 3 , etc.) cause voltage stress on the inverter devices, and, instantaneous reversal in DC link current. Also, as a result of 58
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POLITECHNIKA WARSZAWSKA WARSAW UNIV
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Contents 1. Introduction 4 2. Mathe
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1. Introduction 1. INTRODUCTION The
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Page 9 and 10: 2. Mathematical description of indu
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5. Speed estimation of induction mo
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5.3.1.2. Improved method based on t
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Therefore, the discrete model of st
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6. ANN sensorless Field Oriented Co
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7. Simulation and experimental resu
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8. Conclusions 8. CONCLUSIONS The r
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References REFERENCES Books and Ove
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References [34] D. Schauder, and R.
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References [66] A. Tripathi and P.
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References [97] J. W. Kolar, H. Ert
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References [129] M. P. Kazmierkowsk
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A1. Description of the simulation p
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A2. Laboratory setup A2. Laboratory
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A2. Laboratory setup A2.3. dSpace D
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A2. Laboratory setup Offset calibra
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A2. Laboratory setup consists of an
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A3. Motor parameters A3. MOTOR PARA
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A4. Notation - u s - stator voltage
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POLITECHNIKA WARSZAWSKA

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