Application of Improved Hybrid Particle Swarm optimization Algorithm in Model Identification of Micro Gas Turbine

Micro gas turbine model is generally nonlinear multivariable strong coupling high-order large delay and has other characteristics. How to build the model is one of the hot and difficult issues at this stage. The co-evolution strategy and Gaussian disturbance strategy are introduced into particle swarm optimization algorithm to improve the convergence stability, convergence accuracy and the probability of jumping out of the local optimal solution. It has a certain application value for parameter identification of micro gas turbine model and meets the actual needs of model establishment, which lays a foundation for the subsequent prediction, control, evaluation and analysis of the equipment.