ADAPTIVE INTELLIGENT CONTROL OF AIRCRAFT DYNAMIC SYSTEMS WITH A NEW HYBRID NEURO-FUZZY-FRACTAL APPROACH

摘要

We describe in this paper a hybrid method for adaptive model-based control of nonlinear dynamic systems using Neural Networks, Fuzzy Logic and Fractal Theory. The new neuro-fuzzy-fractal method combines Soft Computing (SC) techniques with the concept of the fractal dimension for the domain of Non-Linear Dynamic System Control. The new method for adaptive model-based control has been implemented as a computer program to show that our neuro-fuzzy-fractal approach is a good alternative for controlling non-linear dynamic systems. It is well known that chaotic and unstable behavior may occur for non-linear systems. Normally, we will need to control this type of behavior to avoid structural problems with the system. We illustrate in this paper our new methodology with the case of controlling aircraft dynamic systems. For this case, we use mathematical models for the simulation of aircraft dynamics during flight. The goal of constructing these models is to capture the dynamics of the aircraft, so as to have a way of controlling this dynamics to avoid dangerous behavior of the aircraft dynamic system.