Generalized Predictive Control Based on Complex Systems Adaptive

In the actual industrial production process, the system of the controlled object often there´s a lot of uncertainty due to some reason, for this kind of system, the traditional method is difficult to follow the change of model parameters in real time. Based on this, this paper presents a complex system of adaptive ladder type of generalized predictive control scheme by using controlled system to cat clustering method of fuzzy identification structure and identifying model set the ladder (multiple model adaptive generalized predictive control scheme), to solve the uncertainty of the system, then for each performance index of the sampling time of switching the choice of optimal controller was realized, and at the same time in order to realize the system global optimal control, and design the ladder type of generalized predictive controller, the final design simulation experiment to validate, the results show that the model has unique advantages compared to other methods.