A Global Convergent Genetic Algorithm and Its Application on Parameters Optimization of Nozzle Area Regulator

摘要：

A Fuzzy Adaptive Simulated Annealing Genetic Algorithm with Gradient direction (GFASAGA) will be proposed in this paper, whose global convergence was analyzed as well. The fuzzy controller parameters of certain aeroengine nozzle area regulator were optimized by GFASAGA, the standard genetic algorithm (SGA) and the hybrid optimization algorithm in iSIGHT comparatively, the results show that: the improved genetic algorithm is of good characteristics, such as global search, evolutionary rapidity and so on;and the resultant nozzle area regulator is provided with good static and dynamic characteristics.

关键词： nozzle area regulator fuzzy control genetic algorithm hybrid optimization algorithm global convergenc Markov chain

作者: PENG Kai FAN Ding YANG Fan HU Xiao-lu

作者单位: School of Power and Energy,Northwestern Polytechnical University,Xian, China

会议类型: 国际会议

会议名称: 4th International Symposium on Jet Propulsion and Power Engineering(第四届喷气推进与动力工程国际会议 ISJPPE2012)

会议地点: 西安

会议语种:英文

页码: 643-647

在线出版日期: 2012-09-10（万方平台首次上网日期，不代表论文的发表时间）