Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Approximation Reduction Based on Similarity Relation
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Fuzzy Systems Engineering: Toward Human-Centric Computing
Fuzzy Systems Engineering: Toward Human-Centric Computing
Time series forecasting through rule-based models obtained via rough sets
Artificial Intelligence Review
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
| Hi-index | 0.00 |
This paper addresses a new approach to design rule-based controllers using concepts of rough sets and techniques of state feedback. The goal is to obtain rule-based models that allow the construction of control loops, ensuring stable conditions and suitable dynamic characteristics for nonlinear systems. The study performs a comparison of the procedure proposed with results obtained with a conventional control, where a system with nonlinear behavior is used. Numerical examples derived from computer simulations and real applications are shown. Experiments in a level plant were performed, checking the potential of the rule-based controllers.