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Design and Application of Fractional Order Predictive Functional Control for Industrial Heating Furnace
Author(s) -
Xiaomin Hu,
Qin Zou,
Hongbo Zou
Publication year - 2018
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.2018.2878554
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
This paper proposes a fractional order predictive functional control method for temperature control of an industrial electric heating furnace. Since the electric heating furnace is affected by complex factors such as measurement noise, uncertainty, model/plant mismatches, and so on, it is more important to derive accurate modeling and controller design for improved control performance. Under the uncertain facts, conventional control methods based on integer order models may not offer the desirable control performance. The fractional order model of the heating furnace based on the input-output data of the step response test is introduced to describe the dynamics of the process and the Oustaloup approximation is used to transform the fractional order process into an integer formulation. Then a predictive functional controller is designed through minimizing the future predicted output error based on the state space model transformation. Application has been implemented on the industrial heating furnace and the experimental tests reveal the validity of the proposed controller in comparison with conventional integer model-based PFC.

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