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

Abstract

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 nz 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 nz is too fast. All of these satisfy the flying safety demand.