Engine Performance Simulation Using Improved PSO Algorithm
Turbo fan engine is a highly complex nonlinear system,thus it is difficult to solve engine mathematical model with traditional iteration methods as these methods are very sensitive to initial values.Therefore particle swarm optimization is used to solve the model and an improved particle swarm optimization algorithm is proposed.Moreover the immune mechanism is introduced with the new algorithm.Next,clone selection mechanism based on logistic chaotic mutation and diversity maintenance based on probability have been designed.Results show that the proposed algorithm has better searching performance and convergence speed than other compared algorithms when modeling a mixed exhaust turbofan engine.
engine simulation particle swarm optimization immune algorithm clone selection
Yonghua Wang Feixiang Zhu
Graduate Student Brigade Naval Aeronautical and Astronautical University Yantai, China
国际会议
成都
英文
1416-1420
2012-06-15（万方平台首次上网日期，不代表论文的发表时间）