Description: Abstract: Researchers at the U.S. Bureau of Mines (USBM) have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by loosely modeling the search procedures of natural genetics. FLC's are rule-based systems that efficiently manipulate a problem environment by modeling the "rule-of-thumb" strategy used in human decisionmaking. Together, GA's and FLC's include all of the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a cont element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and an adaptive element to adjust to the changes in the problem environment. The control system also employs a computer simulation of the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented; all results are from the physical laboratory system and not from a computer simulation.
Creator: Karr, Charles L.; Gentry, E. J. & Stanley, D. A.
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