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Constraint-Based Fuzzy Models for an Environment with Heterogeneous Information-Granules

  • Artificial Intelligence
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Abstract

A novel framework for fuzzy modeling and model-based control design is described. Based on the theory of fuzzy constraint processing, the fuzzy model can be viewed as a generalized Takagi-Sugeno (TS) fuzzy model with fuzzy functional consequences. It uses multivariate antecedent membership functions obtained by granular-prototype fuzzy clustering methods and consequent fuzzy equations obtained by fuzzy regression techniques. Constrained optimization is used to estimate the consequent parameters, where the constraints are based on control-relevant a priori knowledge about the modeled process. The fuzzy-constraint-based approach provides the following features. 1) The knowledge base of a constraint-based fuzzy model can incorporate information with various types of fuzzy predicates. Consequently, it is easy to provide a fusion of different types of knowledge. The knowledge can be from data-driven approaches and/or from control-relevant physical models. 2) A corresponding inference mechanism for the proposed model can deal with heterogeneous information granules. 3) Both numerical and linguistic inputs can be accepted for predicting new outputs.

The proposed techniques are demonstrated by means of two examples: a nonlinear function-fitting problem and the well-known Box-Jenkins gas furnace process. The first example shows that the proposed model uses fewer fuzzy predicates achieving similar results with the traditional rule-based approach, while the second shows the performance can be significantly improved when the control-relevant constraints are considered.

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Correspondence to K. Robert Lai.

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K. Robert Lai was born in 1955. He received his M.S. degree in computer science from Ohio State University, USA, in 1982, and Ph.D. degree in computer science from North Carolina State University, Raleigh, N.C., USA, in 1992. In 1994, he joined Yuzn Ze University, where he is now an associate professor. His current research interests are in agent technologies, and wireless networking.

Yi-Yuan Chiang was born in 1969. He received his M.S. degree in mathematics from Chung Yuan Christian University, Taoyuan, in 1996. He is presently working toward a Ph.D. degree in computer science and engineering at Yuan Ze University. His current research interests include intelligent control and fuzzy constraints.

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Lai, K.R., Chiang, YY. Constraint-Based Fuzzy Models for an Environment with Heterogeneous Information-Granules. J Comput Sci Technol 21, 401–411 (2006). https://doi.org/10.1007/s11390-006-0401-5

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  • DOI: https://doi.org/10.1007/s11390-006-0401-5

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