Autors: Yordanova, S. T.
Title: TSK Model-based Fuzzy Logic Control of Carbon Dioxide Concentration in Rooms
Keywords: Carbon dioxide concentration, genetic algorithms, MATLAB, real-time control, parallel distributed compensation, stability analysis, Takagi–Sugeno–Kang modelling

Abstract: The proper carbon dioxide concentration in premises is one of the factors for the indoor climate comfort. Its control via ventilation depends on the quality of the fresh air used and is accompanied by high energy consumption. The plant is nonlinear with no reliable and simple plant model which makes the design of a linear controller difficult. The model-free fuzzy logic controllers (FLCs) successfully tackle such problems. In the present paper, an FLC based on the principle of parallel distributed compensation is designed to enhance the controller’s tuning, to further improve the control system performance and energy efficiency and to enable its stability analysis. It uses a Takagi–Sugeno–Kang plant model derived from plant input–output experimental data with the help of genetic algorithms optimization.



    Mechatronic Syst.&Contr, vol. 46, issue 1, pp. 32-38, 2018, Canada,

    Цитирания (Citation/s):
    1. E. Yazid, M. Garratt, F. Santoso (2019) Position control of a quadcopter drone using evolutionary algorithms-based self-tuning for first-order Takagi–Sugeno–Kang fuzzy logic autopilots , Applied Soft Computing Journal 78, pp.373-392, - 2019 - в издания, индексирани в Scopus или Web of Science

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