Robust neural network controller for variable airflow volume system

The neural network technology, that is based on the operating mechanism of the human brain, is the best suited technology to enhanced the PID control function. However, it is important to address stability and disturbance properly, to obtain optimal performance of the control system. The paper discusses the design and application of a robust neural network algorithm, and how it compliments the fixed proportional control algorithm to provide the desired functionality and the adaptation of the VAV control system for a wide range of disturbances and parameter changes.