Aircraft longitudinal Critical State Limiter Based on Adaptive Neural Fuzzy Inference System

摘要

Aircraft Pitching CSL (Critical State Limiter) is used to restrict the joystick's longitudinal displacement when a certain flight parameter oversteps the critical allowable value. It is a very important device to assure flying safety. In this paper, a design method of aircraft longitudinal CSL based on ANFIS (Adaptive Neural Fuzzy Inference System) is introduced. The simulation results (H=10km,Ma=0.8/1.5) show: 1. When pilot moves the joystick stably (2°/s), angle of attack α and plumb overload z n gradually grow until one of them oversteps the accepted value, and the joystick displacement is limited at last. 2. When pilot moves the joystick quickly (4°/s), the piston driver of Servo Mechanism can also tail after the movement of joystick at a rapid, and tends to become stabilization in 2-3 seconds. But after 5-7 seconds, the positive feedback appears in system, that is, the output of Servo Mechanism is limited. 3. When pilot moves the joystick fiercely (8°/s), joystick displacement will be limited ahead of time because the change of α or z n is too fast. All of these satisfy the flying safety demand.