Fuzzy-genetic controller for a coupled drives system

The problem of the interaction of MIMO systems has not yet been resolved completely under any methodology, due to its several inconveniences such as a deterioration in the rejection to disturbances, a considerable effort in the analysis when the model is complex, and because it is also necessary that the said model is lineal. The preferred system in this article is a laboratory prototype that emulates industrial processes that involve continuous material transfer, (just as in rolling mills, paper mills and wire manufacturing plants) whose linear model has several differences with the actual behavior of the system, due to nonlinear characteristics. For this reason it is not enough to use conventional techniques, and therefore a Takagi-Sugeno-type fuzzy control is implemented with rules which are optimized by a genetic algorithm. By means of this optimization, a considerable reduction of the interaction in the controlled part is carried out implicitly, thanks to the indirect consequences of the aptitude function construction proposed for the genetic algorithm.