基于PSO算法的航空发动机起动燃油控制
A new method to control fuel flow of aircraft engine's starting process based on PSO Algorithm
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摘要: 针对航空发动机起动过程燃油流量优化控制的实时性要求, 提出一种新的航空发动机起动燃油控制方法——基于粒子群优化（PSO）算法的非线性预测控制.该方法在建立最小二乘支持向量机（LS-SVM）预测模型的基础上, 运用PSO算法实现其滚动优化功能.经实例验证, 燃油流量经过PSO算法优化控制后, 高低压转子转速的超调量减小, 并且其稳定的时间比没有经过优化控制的要快上56 s.由仿真结果可知, 该方法可以用于航空发动机起动过程燃油控制, 当给定的约束条件足够精确时, 能以较高的精度计算出最佳供油规律.Abstract: In order to solve the real time application demand of the fuel flow control in aircraft engine's starting process,a new nonlinear predictive control method based on particle swarm optimization(PSO) algorithm is presented.The method established a predictive model with last suares support vector machines(LS-SVM),and then carried out the receding horizon optimization with PSO algorithm.The example validated that the new control method can reduce the rotors' rotating speed fluctuation and the steady state can be attained 5～6 seconds earlier than that without optimization.The result of the emulation shows that the method is suitable for the fuel flow control,and it can achieve the best control pattern of fuel flow when the restriction is provided accurately.
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[1] 屠秋野,唐狄毅.涡扇发动机起动模型及起动控制规律的研究[J].推进技术,1999,20(2):21-24.TU Qiuye,TANG Diyi.Study on startup model and control law of turhofun engine[J].Journal of Propulsion Technology,1999,20(2):21-24. [2] 余波.航空发动机起动过程控制研究[D].西安:空军工程大学,2006. [3] Kennedy J,Eberhart R.Particle swarm optimization[R].In:IEEE Int'Iconfon Neural Networks,1995. [4] 沈艳,郭兵,古天祥.粒子群优化算法及其与遗传算法的比较[J].电子科技大学学报,2005,34(5):696-699.SHEN Yan,GUO Bing,GU Tianxiang.Partical swarm optimization algorithm and comparison with Genetic Algorithm[J].Journal of UEST of China,2005,34(5):696-699. [5] Suykens J A K,Vandewalle J,De M B.Optimal control by least squres support vector machines[J].Neural Networks,2001,14(1):23-25. -
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