Autors: Yordanova, S. T.
Title: Intelligent Approaches for Linear Controllers Tuning with Application to Temperature Control
Keywords: Fuzzy logic supervisor, genetic algorithms, MATLAB real time temperature control, PI/PID controllers on-line auto-tuning, T-S plant modeling

Abstract: Despite the new sophisticated controllers the linear 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. Various enhancements have been suggested to enlarge their range of operation with good performance.Fuzzy logic (FL) and genetic algorithms (GA) 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 an engineering method for the design of a FL two-level controller (FTLC)of a linear PI/PID controller and a FL supervisor that tunes on-line the PI/PID controller’s gains. The FTLC parameters are off-line optimized using GA and a proposed fitness function for system performance and energy efficiency.The method is tested in real time control of the temperature in a laboratory dryer.

References

    Issue

    Journal of Intell. and Fuzzy Systems, vol. 27, issue 6, pp. 2809-2820, 2014, Netherlands, ISSN: 1064-1246, DOI: 10.3233/IFS-141242

    Цитирания (Citation/s):
    1. Pădureanu I, Jurcu M, Campian C V, Haţiegan C (2017) Determination of the performance of the Kaplan hydraulic turbines through simplified procedure. Int. Conf. on Applied Sciences (ICAS2017), IOP Conf. Series: Materials Science and Engineering 294 (2017) 012027 doi:10.1088/1757-899X/294/1/012027 - 2017 - в издания, индексирани в Scopus или Web of Science
    2. Wellington Mazer,Maryangela G. Lima, Ronaldo A. Medeiros-Junior (2018)Fuzzy logic for estimating chloride diffusion in concrete, Proceedings of the Institution of Civil Engineers - Structures and Buildings 171(7,)pp.542-551, ISSN 0965-0911, E-ISSN 1751-7702, https://doi.org/10.1680/jstbu.16.00153 - 2018 - в издания, индексирани в Scopus или Web of Science

    Вид: статия в списание, публикация в издание с импакт фактор