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| A Fuzzy Modeling Method Based on T-S Model for Blast Furnace Gas System |
| SHENG Chun-Yang, ZHAO Jun, WANG Wei, LIU Ying |
| (College of Control Science and Engineering, Dalian University of Technology, Dalian 116023, China) |
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Abstract Aiming at the modeling problem for blast furnace gas system in steel industry, a class of complex non-linear system, a data-based fuzzy modeling method was proposed. Firstly, the proposed method establishes the identification model based on T-S fuzzy model. Considering the manual interference from the adjustable gas users, a conditional fuzzy clustering is adopted to partition the input and output space. With the introduction of fuzzy concept, the proposed model is adaptive for industrial noises. Then, a Bayesian linear regression is proposed to determine the parameters of the consequent part in this study, which can effectively avoid the ill-conditioned phenomenon. A series of simulation verification by using the industrial data of a certain blast furnace gas system demonstrate that the proposed method exhibits well performance for identifying the blast furnace gas system, and can also be used to optimize, control and schedule the blast furnace gas system.
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Received: 28 May 2012
Published: 29 December 2012
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