Solving Harmonic Elimination Equations in Multi-level Inverters by using Neural Networks
Keywords:
Artificial neural networks, solving algorithm, harmonic elimination algorithm, multilevel inverter.Abstract
Pulse Width Modulation (PWM) using the
harmonic elimination technique needs the solving of a nonlinear
transcendental equations system. Conventionally, due to their
high complexity, these equations have to be solved off-line and
the calculated optimal switching angles are stored in look-up
tables or interpolated by simple functions for real-time
operation. System flexibility is very limited, especially for
applications which require both amplitude and frequency
control. A new implementation scheme based on real-time
solving of the nonlinear harmonic elimination equations using
feed forward Artificial Neural Networks (ANNs) is reported in
this paper. Based on the well known Back-propagation
Algorithm (BPA), two training schemes for the ANN are
presented. In the first one, the ANN is trained using the desired
switching angles given by the classical method. The second
training scheme is developed using only the harmonic
elimination equation systems. Some simulation results are given
to show the feasibility, performances and technical advantages
of the proposed method.
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