Determine the optimal switching angles symmetrical cascaded multilevel inverter using Improved particle swarm optimization algorithm

With the increasing use of inverters in the industry, the need to reduce the output harmonics is felt more than ever. Interstellar multi-level structures have grown exponentially due to benefits such as harmonic reduction and loss reduction. In multi-level inverters, nonlinear and complex equations become more complex when the number of surfaces increases. One of the ways to find optimal keying angles is to reduce the harmonics of the whole Newton-Raphson method. One of the main disadvantages of the Newton-Raphson method is the strong dependence of the answers to the initial guesses. By choosing different initial guesses, different answers may be obtained or results will not converge. And their solution is not possible by conventional methods of numerical solution of nonlinear equations such as the Newton-Ruffson method. In this thesis, one of a variety of Intelligent Algorithms is used to solve the Newton-Raphson method problem. The particle swarm algorithm has been selected based on the proper background in solving problems of high complexity to solve the problem of optimal keying angles in this dissertation. In this thesis, the particle swarm algorithm has been improved. Simulation results for various multilevel converters have been presented and represent the high efficiency of the improved type of particle swarm algorithm in determining the appropriate angle of fire for reducing the high harmonics and generating a waveform with very low harmonic distortion and near sinusoidal.