NDLI: Intelligent control applications in the chemical and power industries

Content Provider	IEEE Xplore Digital Library
Author	VanLandingham, H.F.
Copyright Year	1996
Description	Author affiliation: Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA (VanLandingham, H.F.)
Abstract	Problems found in the electric power and petrochemical industries can be very challenging for control engineers. This paper focuses on two distinct types of problems; namely, sensor redundancy and set-point control. For the latter problem the workhorse of the industry is the 3-element proportional-integral-derivative (PID) controller which can be tuned to provide reasonable performance over a relatively wide range of operation and control problems. PID controllers can, however, become detuned over time as operators continually make minor adjustments. Solutions to these problems of sensor redundancy and self-tuning controllers are discussed using artificial neural networks (ANNs), which can learn in a static mode for the case of sensor redundancy, or dynamically (on-line) in the case of self-tuning adaptation.
Starting Page	63
Ending Page	66
File Size	440337
Page Count	4
File Format	PDF
ISBN	0780331095
DOI	10.1109/MELCON.1996.550964
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-05-16
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent control Industrial control Three-term control Pi control Proportional control Petrochemicals Chemical industry Power engineering and energy Chemical sensors Intelligent sensors
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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