Abstract:

This article presents a study of the real-time optimization algorithm for the performance seeking control(PSC) of aeroengines. An improved real-time optimization algorithm based on the filled function method (FFM) is proposed to solve normal nonlinear optimization problems, which may provide a better solution than the current local minima do in the optimization process by constructing some filled functions constantly, and the above mathematical mechanism leads to the FFM optimization algorithm which has more powerful global convergence ability than the traditional programming methods. The numerical recipe about this algorithm is introduced in detail in this article. As a simulation example, the improved FFM optimization algorithm is used in the minimum specific fuel consumption control mode in afterburning condition for a certain two-spool turbofan engine’s performance seeking control, and the simulation results show that it is more efficient and reliable to find global minima by the proposed algorithm than the traditional sequential linear programming method.

Key words: aeroengine, performanceseekingcontrol, filledfunctionmethod, globalconvergenceability, minimumspecificfuelconsumptionmode