Fuzzy system modeling using linear distance rules
Fuzzy Sets and Systems
Structure identification and parameter optimization for non-linear fuzzy modeling
Fuzzy Sets and Systems - Fuzzy systems
Application of evolving Takagi-Sugeno fuzzy model to nonlinear system identification
Applied Soft Computing
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
T-S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
A transformed input-domain approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems
A chaotic digital secure communication based on a modified gravitational search algorithm filter
Information Sciences: an International Journal
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Hydraulic turbine governing system (HTGS) is a complicated nonlinear system that controls the frequency and power output of hydroelectric generating unit (HGU). The modeling of HTGS is an important and difficult task, because some components, like hydraulic turbine and governor actuator, are with strong nonlinearity. In this paper, a novel Takagi-Sugeno (T-S) fuzzy model identification method based on chaotic gravitational search algorithm (CGSA) is proposed and applied in the modeling of HTGS. In the proposed method, fuzzy c-regression model clustering algorithm is used to partition the input space and identify the coarse antecedent membership function (MF) parameters at first. And then, a novel CGSA is proposed to search better MF parameters around the coarse results, in which chaotic search has been embedded in the iteration of basic GSA to search and replace the current best solution of GSA. The performance of the proposed fuzzy model identification method is validated by benchmark problems, and the results show that the accuracies of identified models have been improved significantly compared with the other existing models. Finally, the proposed approach has been applied to approximate the dynamic behaviors of HTGS of a HGU in a hydropower station of Jiangxi Province of China. The experimental results show that our approach can identify the HTGS satisfactorily with acceptable accuracy.