POLITECHNIKA WARSZAWSKA

4. ANN based Current Controllers
4.3. Off-line trained neural comparator
4.3.1. Introduction
In this section the application of off-line trained ANN working as a comparator in
current control loop of the PWM inverter will be presented. This idea has been
published by Harashima et al [115]. In this section this idea will be developed and
extended. In the first part, the configuration presented is the same as in [115] and a
block scheme of this system is shown. In the second part, in contrast to the previous
approach, we will introduce controller working in α-β coordinates. Finally simulation
results will be presented, and comparative study with delta modulator and hysteresis
comparators will be carried out. The new solutions based on the perceptron will be
presented as well, and will be shown, that such a simple NN is enough to implement
the Delta Regulator.
4.3.2. NN controller in three phase ABC coordinates
4.3.2.1. Current control scheme
Harashima et. al. [115] have proposed NN regulator (Fig. 4.10b) which should have
similar input-output relation to that of the hysteresis comparator (Fig. 4.10a).
The three layer (3-5-3 architecture) feedforward NN has been trained according to the
rules given in the Table 4.2 using back propagation algorithm [149].
After learning process, when the errors between the desired output and the actual NN
output were less than 1%, the NN has been applied as current regulator. However, for
the three phase symmetrical load (without zero leader) the sum of the instantaneous
current errors is always zero:
ε A
+ ε B
+ ε C
= 0
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