Intelligent Industrial Furnace Control Using Model-Free Adaptive Control Technology

In the United States, industrial plants consume more energy than any other sector, including the building and transportation sectors. Manufacturers of commodity materials and products ¿ such as metals, glass, chemicals, and paper ¿ consume more than 70% of all energy consumed in the industrial sector. Thus, energy savings in these plants can have a big impact on our nation¿s energy security, economic health, and carbon mitigation. Industrial furnaces, the largest energy consuming operating units in industrial plants, heat raw materials such as crude for oil refining, and materials such as steel and glass for product forming. However, most furnaces are not well controlled: over-heating and poor combustion control is common, causing energy wastes, low efficiency, and product defects. Moreover, a large furnace typically has multiple interacting temperature zones, its processes are typically nonlinear, and it is subject to large time delays, load and fuel disturbances, and changes in operating conditions. This project will develop an intelligent control solution for large-scale industrial furnaces that can effectively (1) control large-scale interacting temperature zones; (2) deal with changes in load, fuel, and operating conditions; and (3) achieve optimal combustion. Commercial Applications and other Benefits as described by the awardee: The technology should enable U.S. industrial plants to save energy, improve efficiency and quality, and maintain a competitive edge. Since industrial furnaces are widely used in almost every industrial plant, the importance of improving control performance cannot be overstated.