Fuzzy Sets and Systems - Control and applications
Decoupled fuzzy controller design with single-input fuzzy logic
Fuzzy Sets and Systems - Control and applications
Center Manifold Theory Approach to the Stability Analysis of Fuzzy Control Systems
Proceedings of the 6th International Conference on Computational Intelligence, Theory and Applications: Fuzzy Days
Integrating expert knowledge into industrial control structures
Computers in Industry - Special issue: Soft computing in industrial applications
Computers in Industry - Special issue: Soft computing in industrial applications
Stability Analysis of a Simple-Structured Fuzzy Logic Controller
Journal of Intelligent and Robotic Systems
PI-Fuzzy controllers for integral plants to ensure robust stability
Information Sciences: an International Journal
Adaptive fuzzy logic controller for DC-DC converters
Expert Systems with Applications: An International Journal
Optimisation criteria in development of fuzzy controllers with dynamics
Engineering Applications of Artificial Intelligence
Issues concerning the analysis and implementation of a class of fuzzy controllers
Fuzzy Sets and Systems
Three-dimensional min--max-gravity based fuzzy PID inference analysis and tuning
Fuzzy Sets and Systems
A neural fuzzy framework for system mapping applications
Knowledge-Based Systems
A novel fuzzy framework for nonlinear system control
Fuzzy Sets and Systems
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
An error-based on-line rule weight adjustment method for fuzzy PID controllers
Expert Systems with Applications: An International Journal
Online tuning of fuzzy PID controllers via rule weighing based on normalized acceleration
Engineering Applications of Artificial Intelligence
Information Sciences: an International Journal
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It has been proved that fuzzy controllers are capable of approximating any real continuous control function on a compact set to arbitrary accuracy. In particular, any given linear control can be achieved with a fuzzy controller for a given accuracy. The aim of this paper is to show how to automatically build this fuzzy controller. The proposed design methodology is detailed for the synthesis of a Sugeno or Mamdani type fuzzy controller precisely equivalent to a given PI controller. The main idea is to equate the output of the fuzzy controller with the output of the PI controller at some particular input values, called modal values. The rule base and the distribution of the membership functions can thus be deduced. The analytic expression of the output of the generated fuzzy controller is then established. For Sugeno-type fuzzy controllers, precise equivalence is directly obtained. For Mamdani-type fuzzy controllers, the defuzzification strategy and the inference operators have to be correctly chosen to provide linear interpolation between modal values. The usual inference operators satisfying the linearity requirement when using the center of gravity defuzzification method are proposed