Parameter Identification of Electro-Hydraulic Servo System of Steam Turbine Based on Improved Particle Swarm Optimization

Electro-hydraulic servo system is an important part of steam turbine speed control system, and whether the parameters are set reasonably is a key step in the process of modeling. Aiming at the advantages and disadvantages of traditional particle swarm optimization algorithm, an improved particle swarm optimization algorithm is proposed for parameter identification of electro-hydraulic servo system of steam turbine. The particle swarm optimization algorithm is improved by carrying out nonlinear processing on the group learning factor, the individual learning factor and the inertia weight in the particle swarm optimization algorithm, optimizing the particle boundary limit and adopting a method of updating different positions for particle classification. In this way the convergence speed of the particle swarm optimization algorithm is effectively improved and the premature convergence problem of the particle swarm optimization algorithm in the boundary aggregation is prevented. The electro-hydraulic servo system of thermal power units is processed systematically, which simplifies the parameter identification steps and is beneficial to obtain more reasonable parameters.