Neural-Network-Based Fuzzy Logic Control and Decision System
IEEE Transactions on Computers - Special issue on artificial neural networks
Fuzzy Sets and Systems
A self-tuning fuzzy controller
Fuzzy Sets and Systems
Fuzzy self-tuning of PID controllers
Fuzzy Sets and Systems
An introduction to fuzzy control
An introduction to fuzzy control
A self-organizing adaptive fuzzy controller
Fuzzy Sets and Systems
PID type fuzzy controller and parameters adaptive method
Fuzzy Sets and Systems
Design and analysis of a fuzzy proportional-integral-derivative controller
Fuzzy Sets and Systems
Fuzzy Control
A fuzzy controller with evolving structure
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Bio-inspired systems (BIS)
Influential Rule Search Scheme (IRSS)-A New Fuzzy Pattern Classifier
IEEE Transactions on Knowledge and Data Engineering
Generalised influential rule search scheme for fuzzy function approximation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
NEFCLASS-based neuro fuzzy controller for SRM drive
Engineering Applications of Artificial Intelligence
Multiobjective evolution based fuzzy PI controller design for nonlinear systems
Engineering Applications of Artificial Intelligence
Direct adaptive self-structuring fuzzy controller for nonaffine nonlinear system
Fuzzy Sets and Systems
Adaptive fuzzy control for uncertain interconnected time-delay systems
Fuzzy Sets and Systems
Conventional fuzzy control and its enhancement
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Design and analysis of region-wise linear fuzzy controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Analysis of direct action fuzzy PID controller structures
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Design of fuzzy controllers with adaptive rule insertion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Neuro-fuzzy hybrid control system of tank level in petroleum plant
IEEE Transactions on Fuzzy Systems
A robust self-tuning scheme for PI- and PD-type fuzzy controllers
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Self-organizing neuro-fuzzy system for control of unknown plants
IEEE Transactions on Fuzzy Systems
Supervisory recurrent fuzzy neural network control of wing rock for slender delta wings
IEEE Transactions on Fuzzy Systems
Modeling and Optimal Control of Batch Processes Using Recurrent Neuro-Fuzzy Networks
IEEE Transactions on Fuzzy Systems
Genetic algorithm-based optimal fuzzy controller design in the linguistic space
IEEE Transactions on Fuzzy Systems
Fuzzy-based adaptive bandwidth control for loss guarantees
IEEE Transactions on Neural Networks
An approximate internal model-based neural control for unknown nonlinear discrete processes
IEEE Transactions on Neural Networks
A learning based self-organized additive fuzzy clustering method and its application for EEG data
International Journal of Knowledge-based and Intelligent Engineering Systems - Intelligent Information Processing: Techniques and Applications
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The present paper describes the development of a new adaptive fuzzy logic controller (AFLC), which can directly employ an adaptive fuzzy/neuro/neuro-fuzzy function approximator to develop a desired controller, based on an ideal controller input-output data set. The system also proposes the development of the AFLC based on a new adaptive fuzzy system, called influential rule search scheme (IRSS), as a pure function approximation tool. The proposed AFLC employs two additional sub-modules: i) a new static fuzzy resetting action controller (FRAC), which fuzzily changes the resetting action of the controller at each sampling instant, to enhance system performance, and ii) a new fuzzy inverse process estimator, based on IRSS as a function approximator itself. Simulation studies are shown to demonstrate the effectiveness of the proposed controller scheme over conventional PID controllers and other existing fuzzy and neural network based controllers.