NDLI: Optimization design of pid controller parameters based on improved E.Coli foraging optimization algorithm

Content Provider	IEEE Xplore Digital Library
Author	Liu Yijian Fang Yanjun
Copyright Year	2008
Description	Author affiliation: Sch. of Electr. & Autom. Eng., Nanjing Normal Univ., Nanjing (Liu Yijian)
Abstract	E.Coli foraging optimization algorithm is an evolutional algorithm and imitates the behavior of E.Coli bacteria. In this paper, a novel improved E.Coli foraging optimization algorithm (IEFOA) for parameter tuning of PID controller has been proposed. IEFOA is presented with three main operators, which include a tumbling operator, a swimming operator and a tracing operator that at the same time records the optimal position of individual E.Coli in order to update the locations of swarm. Instead of using traditional analysis algorithm, the parameters of PID controller such as proportional gain, integral factor, differential coefficient are selected and optimized by IEFOA. The effectiveness of the proposed optimization algorithm is tested by simulation experiments of the common one-order and two-order industrial models. The simulation shows excellent results in term of response time and output overshoot for a step reference. The IEFOA approach provides an attractive method for the design of PID controller parameters.
Starting Page	227
Ending Page	231
File Size	155319
Page Count	5
File Format	PDF
ISBN	9781424425020
DOI	10.1109/ICAL.2008.4636151
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Microorganisms Improved E.Coli Design of Automated Control System Process control Artificial neural networks Modelling Controller Optimization Tuning Genetic algorithms
Content Type	Text
Resource Type	Article

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