Single Neuron PID Control of a Turbofan Engine with Inlet Pressure Distortion

Abstract

In this paper, a preliminary exploration and research about the adaptive control law has been carried on for the turbofan engine with inlet pressure distortion. First, a real-time dynamic component-based model which contains the inlet distortion effects was established. Then, we select a single neuron PID controller with adaptive parameters to complete the dynamic acceleration process. The results illustrate that the single neuron control algorithm with gain adaptive has strong robustness, self-learning and anti-jamming capability and the performance of a turbofan engine can be effectively improved by using the turbine expansion ratio adaptive control law.