Model-Based Application of Fuzzy Control to a Class of Industrial Process Operation Systems With Uncertainty | Zendy

Yang Wang | Zendy; Jinna Li | Zendy; Huiyong Wu | Zendy

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Model-Based Application of Fuzzy Control to a Class of Industrial Process Operation Systems With Uncertainty

Author(s) -

Yang Wang,

Jinna Li,

Huiyong Wu

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2768080

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, the model-based fuzzy control application for double-layer operation systems with uncertainty is addressed. Due to the multiple-time scales of complex industrial systems, as well as the inborn uncertainties of the system, the challenge of feedback control is presented. A new approach based on a class of fuzzy models with uncertainty fulfilling the condition of sector bound for the operation process system is proposed. First, a fuzzy model of the system is considered in terms of the system's described dynamical characteristics, and the PI fuzzy controller is then employed for the model, which will ensure controlled plant tracking set-points. Second, with different sampling rates, a dual-layer model combining PI fuzzy controller and dynamical fuzzy output feedback controller are presented. Third, the S-procedure is applied to derive the feedback controller, which can simultaneously guarantee the mean value of steady-state error between the realistic and target operational index is zero and the stability of the dual closed-loop control system is established. Finally, significant simulations have been executed to show the effectiveness of the proposed approach.

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