Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Fuzzy Modeling for Control
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Fuzzy Model Based Control: Application to an Oil Production Separator
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Fuzzy clustering based models applied to petroleum processes
WSEAS Transactions on Systems and Control
Generating fuzzy rules for target tracking using a steady-stategenetic algorithm
IEEE Transactions on Evolutionary Computation
Nonlinear internal model control: application of inverse model based fuzzy control
IEEE Transactions on Fuzzy Systems
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Methods for generating fuzzy singleton models from input-output data have been proposed by many authors. This paper introduces a genetic algorithm (GA) based method to generate a fuzzy singleton model taking into account all the necessary constraints to guarantee an analytically inverted representation of the process dynamics which may be used as a fuzzy controller in Internal Model Control (IMC) strategy. A major advantage of this sort of models is its high interpretability compared to first-order Takagi-Sugeno fuzzy models generated from fuzzy clustering techniques [15]. The proposed method is applied to a liquid level control problem in an oil production separator based upon real input-output data, where obtaining an adequate fuzzy model is of crucial importance.