Controlling chaotic and unstable behavior in non-linear biochemical reactors by using a new neuro-fuzzy-fractal approach

Describes a method for adaptive model-based control of non-linear dynamic plants in the food industry using neural networks, fuzzy logic and fractal theory. The neuro-fuzzy-fractal method combines soft computing (SC) techniques with the concept of the fractal dimension for the domain of non-linear dynamic plant 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 plants. We illustrate our methodology with the case of controlling biochemical reactors in the food industry. For this case, we use mathematical models for the simulation of bacteria growth for several types of food