A new neuro-fuzzy-fractal approach for adaptive model-based control of non-linear dynamic systems: the case of controlling aircraft dynamics

Abstract

Describes a general method for adaptive model-based control of non-linear 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. We illustrate our 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 system.