Fuzzy self-organizing controller and its application for dynamic processes
Fuzzy Sets and Systems - Fuzzy Control
Experiments with the use of a rule-based self-organising controller for robotics applications
Fuzzy Sets and Systems - Fuzzy Control
International Journal of Approximate Reasoning
A rule self-regulating fuzzy controller
Fuzzy Sets and Systems
Control of dynamical processes using an on-line rule-adaptive fuzzy control system
Fuzzy Sets and Systems
Control of dynamic systems using fuzzy learning algorithm
Fuzzy Sets and Systems
Self-tuning fuzzy-controller for process control in internal grinding
Fuzzy Sets and Systems - Special issue on industrial applications
Neural networks in designing fuzzy systems for real world applications
Fuzzy Sets and Systems
Fuzzy adaptive learning control network with on-line neural learning
Fuzzy Sets and Systems - Special issue on fuzzy control
A GA paradigm for learning fuzzy rules
Fuzzy Sets and Systems - Special issue on connectionist and hybrid connectionist systems for approximate reasoning
Genetic algorithms based fuzzy controller for high order systems
Fuzzy Sets and Systems
Controlling the power output of a nuclear reactor with fuzzy logic
Information Sciences: an International Journal
International Journal of Advanced Intelligence Paradigms
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From 1995–1999 a R&D project on fuzzy control applications to the Belgian Reactor 1 (BR1) was conducted at the Belgian Nuclear Research Centre (SCK·CEN). Due to the safety regulations of the nuclear reactor, it is not realistic to perform many experiments at BR1. In this situation, part of the pre-processing experiments had to be carried outside the reactor (e.g., comparisons of different methods and the preliminary choices of the parameters). Therefore a water-level control system, referred to as a real-time control demo-model, was designed and constructed. In this paper, the construction of the demo-model and related hardware aspects is firstly outlined, then the results of a fuzzy control (Mamdani-type) and an adaptive fuzzy control are presented. The adaptive fuzzy control is a fuzzy control with an adaptive function that can self-regulate the fuzzy control rules. Finally, an implementation of a computer simulation is introduced with an adaptive fuzzy control for this real-time control demo-model.