Solving Harmonic Elimination Equations in Multi-level Inverters by using Neural Networks
Pulse Width Modulation (PWM) using the harmonic elimination technique needs the salving 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.
Artificial Neural Networks Solving Algorithm Harmonic Elimination Algorithm Multilevel Inverter
Omar Bouhali Nassim Rizoug
Department of Automatic, LAMEL Laboratory Jijel University Ouled-aissa, P.O. Box 98, Jijel 18000, Al Mecatronic Laboratory ESTACA-Laval BP 76121, 53061 Laval Cedex 9
国际会议
成都
英文
1505-1510
2010-12-17（万方平台首次上网日期，不代表论文的发表时间）