信赖域滤子算法在航空发动机在线优化中的应用

主要研究了航空发动机在线优化问题.以非线性发动机部件级模型为优化对象,将信赖域滤子算法应用于航空发动机在线优化,相比基本信赖域算法,该算法由于采用非单调的滤子算法和松弛重置,兼顾了算法在目标函数值下降与可行性保持两方面的品质,通过松弛重置避免子问题的不可行性,滤子算法则保证了算法收敛到全局最小解.最后,基于信赖域滤子算法,以涡扇发动机最小油耗寻优控制为仿真算例,验证了该算法的优越性.

Application of trust region filter algorithm to aero-engine online optimization

Online optimization method for aero-engine was mainly studied in this paper.Trust region filter algorithm was applied to solve aero-engine online optimization problem in which a relative nonlinear component-level model was used as the optimization model.The algorithm has better optimality and feasibility than the basic trust region algorithm(BTRA).Sub optimization problem infeasibility is escaped by using a restoration algorithm,and the filter algorithm guarantees the algorithm global convergence ability.As shown in a simulation example,the trust region filter algorithm was used in the minimum specific fuel consumption mode for some two-spool turbofan engine performance seeking control,and the simulation results show that it has better optimization effectiveness than BTRA,if it's intended to solve aero-engine online optimization problem.