Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Evaluating controller robustness using cell mapping
Fuzzy Sets and Systems - Special issue on formal methods for fuzzy modeling and control
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Fuzzy Logic and Intelligent Systems
Fuzzy Logic and Intelligent Systems
Advanced Fuzzy Systems Design and Applications
Advanced Fuzzy Systems Design and Applications
A Model Checking Technique for the Verification of Fuzzy Control Systems
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06) - Volume 01
Automatic Synthesis of Robust Numerical Controllers
ICAS '07 Proceedings of the Third International Conference on Autonomic and Autonomous Systems
IEEE Transactions on Fuzzy Systems
A framework for the automatic synthesis of hybrid fuzzy/numerical controllers
Applied Soft Computing
Hi-index | 0.00 |
Control systems are small components that control the behavior of larger systems. In the last years, sophisticated controllers have been widely used in the hardware/software embedded systemscontained in a growing number of everyday products and appliances. Therefore, the problem of the automatic synthesis of controllers is extremely important. To this aim, several techniques have been applied, like cell-to-cell mapping, dynamic programmingand, more recently, model checking. The controllers generated using these techniques are typically numerical controllersthat, however, often have a huge size and not enough robustness. In this paper we present an automatic iterative process, based on genetic algorithms, that can be used to compress the huge information contained in such numerical controllers into smaller and more robust fuzzy control systems.