Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Yordanova, Snejana
Affiliations: Faculty of Automation, Technical University of Sofia, Sofia, Bulgaria
Note: [] Corresponding author. Snejana Yordanova, Faculty of Automation, Technical University of Sofia, 8 Kliment Ohridski blvd., Sofia 1000, Bulgaria. Tel.: +359 02 965 3313; Fax: +359 02 965 2447; E-mail: [email protected]
Abstract: Despite the new sophisticated controllers the linear PI/PID controllers keep the leading position in industrial implementations due to their simplicity, easy and well developed design and tuning, good system performance and robustness and universal application area. Various enhancements have been suggested to enlarge their range of operation with good performance. Fuzzy logic (FL) and genetic algorithms (GAs) offer proper intelligent solutions for improving the PI/PID controllers auto- tuning and adaptation to successfully deal with plant nonlinearity, inertia and changing parameters without plant model. The aim of this research is to develop a simple for engineering use method for design of a fuzzy two-level controller (FTLC) of a linear PI/PID controller and a FL supervisor. The FL supervisor tunes on-line the scaling of the basic PI/PID controller's gains depending on performance indicators. The basic FTLC parameters are off-line optimized using GAs and a proposed fitness function of system performance and energy efficiency which is estimated in system simulation with a GA developed T-S plant model. The method is tested in real time control of the temperature in a laboratory – scale dryer. The result is decreased settling time, overshoot and energy consumption in the whole range of operation of the nonlinear plant.
Keywords: Fuzzy logic supervisor, genetic algorithms, MATLAB™ real time temperature control, PI/PID controllers on-line auto-tuning, T-S plant modeling
DOI: 10.3233/IFS-141242
Journal: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2809-2820, 2014
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]