Abstract
In this paper the author's experience in applying intelligent control in the process industries is discussed. A framework for intelligent control is presented in which intelligent control is defined in a broad sense to include items such as fault detection/isolation, modeling, and optimization. The focus of the paper is on techniques that have proven beneficial in the process industries. Methods utilizing multivariate statistical techniques are presented, with applications to soft sensing, batch process optimization, and fault detection/isolation. Potential problems with closing control loops around soft sensors are also discussed. The second broad technique considered involves model predictive control, and a wastewater application is discussed. Lastly, a brief discussion on expert systems and fuzzy control is presented, and finally a summary is given.
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