Paper
19 October 1987 Use Of A Rule-Based System For Process Control
John A. Bernard
Author Affiliations +
Proceedings Volume 0857, IECON'87:Automated Design and Manufacturing; (1987) https://doi.org/10.1117/12.943271
Event: IECON, Cambridge, 1987, Cambridge, MA, United States
Abstract
A rule-based, digital, closed-loop controller that incorporates 'fuzzy' logic has been designed and implemented for the control of power on the 5 MWt MIT Research Reactor under both steady-state and transient conditions. Based on this experience and having designed several other controllers for the same purpose, a comparison is made of the rule-based and analytic approaches. Differences in the division of labor between plant engineers and control specialists, the type of knowledge required and its acquisition, the use of performance criteria, and controller testing are discussed. The design, implementation, and calibration of rule-based controllers are reviewed with specific examples taken from the completed work at the MIT Research Reactor. An evaluation is then made of the possible role of rule-based technology in process control. It is noted that there are no comprehensive guidelines for the design of rule-based controllers and that such systems are quite difficult to calibrate. The advantage of rule-based systems is that they are generally more robust than their analy-tic counterparts. The rule-based and analytic technologies should therefore be used to complement each other with rule-based systems being employed both as backups to analytic controllers and as a means of improving the man-machine interface by providing human operators with the rationale for automatic control actions.
© (1987) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John A. Bernard "Use Of A Rule-Based System For Process Control", Proc. SPIE 0857, IECON'87:Automated Design and Manufacturing, (19 October 1987); https://doi.org/10.1117/12.943271
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Cited by 8 scholarly publications.
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KEYWORDS
Process control

Rule based systems

Control systems

Calibration

Fuzzy logic

Analytical research

Knowledge acquisition

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