Active Disturbance Rejection Based Iterative Learning Control for Variable Air Volume Central Air-Conditioning System

The Variable Air Volume (VAV) Central Air-Conditioning system is a complicated system with non-linearity, large-time delay and strong inertia, thus it is difficult to design an effective controller. Iterative Learning Control (ILC) takes good effect in controlled process with repeatability and periodicity, but it cannot cope with uncertain disturbance explicitly. A creative algorithm, Active Disturbance Rejection based Iterative Learning Control (ADR-Based ILC), is proposed to improve ILC’s performance in VAV control system. ADR-Based ILC compensates the disturbance explicitly caused by ambient temperature, heat from people and machines, and makes it higher control precision and higher energy-efficiency. An accurate model of VAV system is built in TRNSYS platform, and ADR-Based ILC is proved to be more effective than fuzzy PID and ILC.