Design and Application of Intelligent Predictive Controller Based on MPC Grey Theory Algorithm

With the development and optimization of AI algorithms and prediction models, for complex cross-coupled environments and objects, where it is difficult to establish mathematical models or the accuracy of test methods is not high, it is difficult to ensure effective control scheme operation and algorithm application. Firstly, based on the analysis of the interference model and the prediction principle of intelligent control, empirical Value Theory with MPC (Model Predictive Control) Grey Theory Algorithm, the principle of gray prediction algorithm is the optimal solution of the mean square value of the constraint set. Secondly, the variable input parameters are integrated into a mathematical model for model matching of several segments, the time axis of its control system can establish a complete time model with discrete time series. It is beneficial to analyze and solve complex models or systems that cannot be described by traditional numbers, especially the incomplete or distorted parameter information. Finally, it is concluded that the design of intelligent predictive controller based on MPC gray theory algorithm has better advantaged, it belongs to a multi-valued hybrid dynamic algorithm. Good predictive effect in error adjustment and fluctuation suppression.