An introduction to fuzzy control
An introduction to fuzzy control
Evolving fuzzy rule based controllers using genetic algorithms
Fuzzy Sets and Systems
Evolving rule-based models: a tool for design of flexible adaptive systems
Evolving rule-based models: a tool for design of flexible adaptive systems
Computer Controlled Systems: Theory and Design
Computer Controlled Systems: Theory and Design
A self-learning fuzzy logic controller using genetic algorithms with reinforcements
IEEE Transactions on Fuzzy Systems
Self-constructing fuzzy neural network speed controller for permanent-magnet synchronous motor drive
IEEE Transactions on Fuzzy Systems
Identification of evolving fuzzy rule-based models
IEEE Transactions on Fuzzy Systems
A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
A new adaptive fuzzy controller with saturation employing influential rule search scheme (IRSS)
International Journal of Knowledge-based and Intelligent Engineering Systems
Using a non-uniform self-selective coder for option pricing
Applied Soft Computing
Logic-oriented neural networks for fuzzy neurocomputing
Neurocomputing
Fuzzy Sets and Systems
Computational intelligence approach to PID controller design using the universal model
Information Sciences: an International Journal
An algorithm for online self-organization of fuzzy controllers
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Design of a fuzzy logic controller for a plant of N-order based on genetic algorithms
ROCOM'11/MUSP'11 Proceedings of the 11th WSEAS international conference on robotics, control and manufacturing technology, and 11th WSEAS international conference on Multimedia systems & signal processing
New Online Self-Evolving Neuro Fuzzy controller based on the TaSe-NF model
Information Sciences: an International Journal
Water leakage forecasting: the application of a modified fuzzy evolving algorithm
Applied Soft Computing
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An approach to on-line design of fuzzy controllers of Takagi-Sugeno type with gradually evolving structure is treated in the paper. Fuzzy rules, representing the structure of the controller are generated based on data collected during the process of control using newly introduced technique for on-line identification of Takagi-Sugeno systems. The output of the plant under control (including its dynamic) and the respective control signal has been memorised and stored in on-line mode. These data has been used to train in a non-iterative, recursive way the fuzzy controller. The indirect adaptive control approach has been used in combination with the novel on-line identification technique. This approach exploits the quasi-linear nature of Takagi-Sugeno models and builds-up the control rule-base structure and adapts it in on-line mode with recursive, non-iterative learning. The method is illustrated with an example from air-conditioning systems, though it has wider potential applications.