Fuzzy Control of Printing Color Quality Based on Genetic Algorithm

Aiming at the controlled object with large lag, model uncertainty and time variation due to the effects of working environment in printing process, and printing process requires few adjustment times, this paper designs a T-S fuzzy controller based on the theoretical model of printing color quality control, and uses the genetic algorithm to optimize the initial control rules of fuzzy controller. The optimization method aims at the problems of less known condition and the uncertain effects due to the environmental changes after the first printing. In the process of optimization, the theoretical model of the printing color quality control is used as the controlled object, and the parameters of control rule corresponding to the points of special error are optimized one by one, then the general fuzzy control rules can be got. Finally, an example illustrates the process of this method, and the robustness of the optimized fuzzy controller is analyzed. From the control results got by the optimized fuzzy controller, it can be seen that this method improves the control effects greatly, and reduces adjustment times. Finally, this paper gives some suggestions on its further perfection.