Neural Network Identifier with Fuzzy Logic Compensation for Aero-Engine Rotating Speed Control System

A new neural network algorithm with fuzzy logic compensation was proposed and applied to an aero-engine rotating speed control system.A dynamic neural network was used to identify the plant on-line.The control signal was then calculated iteratively according to the responses of a reference model and the output of identified plant.A fuzzy logic block with four very simple rules was added to the loop to improve the overall loop properties.Experimental results demonstrate that the proposed control strategy provides better disturbance rejection and transient properties than those achieved by conventional mechanical-hydraulic controller and Analogue Engine Electronic Controller(AEEC).At the same time,it can improve transient quality in control system,and meet the requirements of high performance guideline and high control accuracy in turbofan engine.