TSK-Based Linguistic Fuzzy Model with Uncertain Model Output

  • Authors:

  • Keun-Chang Kwak;Dong-Hwa Kim

  • Affiliations:

  • The author is with Intelligent Robot Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Korea. E-mail: kwak@etri.re.kr,;The author is with the Department of Control and Instrumentation Engineering, Hanbat National University, Daejeon, Korea.

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2006

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Abstract

We present a TSK (Takagi-Sugeno-Kang)-based Linguistic Fuzzy Model (TSK-LFM) with uncertain model output. Based on the Linguistic Model (LM) proposed by Pedrycz, we develop a comprehensive design framework. The main design process is composed of the automatic generation of the contexts, fuzzy rule extraction by Context-based Fuzzy C-Means (CFCM) clustering, connection of bias term, and combination of TSK and linguistic context. Finally, we contrast the performance of the presented models with other models for coagulant dosing process in a water purification plant.