Strategy for Adaptive Process Control for a Column Flotation Unit

Researchers at the University of Alabama in cooperation with the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GAS) are used to augment fuzzy logic controllers (FLCs). GAS are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by mimicking the search procedures of natural genetics. FLCs are rule based systems that efficiently manipulate a problem environment by modeling the "rule-of-thumb" strategy used in human decision making. GAS and FLCs can be combined to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. I" this paper, the details of an ongoing research effort to develop and implement an adaptive process control system for a column flotation unit are discussed.