Robust neural network controller for variable airflow volume system

Abstract

In this dissertation work, we concentrate on the analysis of a neural network (NN) tracking controller for the Variable Airflow Volume (VAV) system. A robust weight-tuning algorithm is proposed to train the multi-layered NN with a dead zone scheme. This scheme assures the convergence of the NN tracking error in the presence of disturbance.