Parameter identification of multi-path transmission model for power line communication based on AS-PSO hybrid algorithm

Based on existing power line structures of multi-path transmission channel model and taking the measured data of practical low voltage power-line communication channel magnitude of the frequency response within the range form 0.5MHz to 20MHz as samples, The particle swarm optimization algorithm of self-adaptive parameter based on ant colony algorithm (AS-PSO) is applied to the multi-parameter identification of channel model for low voltage communication channel. By means of the ant colony algorithm the inertia weight parameters achieve self-adapting adjustment and evolution, meanwhile, overcome the shortcoming of easy to occur premature convergence in basic PSO. The parameter identification results of 4-channel and 16-channel models show that by use of the AS-PSO the convergence speed is faster than by genetic algorithm (GA), basic PSO algorithm and the time for the identification is saved, the fitting accuracy is improved. The more number of paths being taken, the better the fitting result will be.