System identification: theory for the user
System identification: theory for the user
Introduction to artificial intelligence and expert systems
Introduction to artificial intelligence and expert systems
Construction of fuzzy models through clustering techniques
Fuzzy Sets and Systems
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Constructing fuzzy models by product space clustering
Fuzzy model identification
Fuzzy Control and Fuzzy Systems
Fuzzy Control and Fuzzy Systems
Neural Fuzzy Control Systems with Structure and Parameter Learning
Neural Fuzzy Control Systems with Structure and Parameter Learning
The development of fuzzy decision trees in the framework of Axiomatic Fuzzy Set logic
Applied Soft Computing
A neuro-fuzzy approach for prediction of human work efficiency in noisy environment
Applied Soft Computing
Cascaded centralized TSK fuzzy system: universal approximator and high interpretation
Applied Soft Computing
Developing a well-being monitoring system-Modeling and data analysis techniques
Applied Soft Computing
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The high complexity of a plant control system related structuring the domain expert knowledge into a knowledge base could decrease task. This paper presents a strategy adopted to model the application of control strategies employed in surveyed companies. Control engineering plays an important part in any industrial plant. Good control and optimisation of correct control strategies is therefore very crucial for the effective running of a control task related establishment of any kind. The control strategy approaches, must be followed right from system identification, modelling, validation, test and implementation. These stages are not always transparent when dealing with a system whose mathematical model does not exist or is difficult to obtain. When faced with this kind of problem, control enhancement techniques, such as knowledge-based, and intelligent system are always an obvious alternative.