Research On Model Predictive Control Based On Cascade Control

The largeness and complication of the industrial development make the request of operating condition become stricter,the correlation between variables become more complicated.These industrial processes should use complicated control systems to satisfy the industrial request. Cascade control system is one of the complicated control systemsModel predictive control is a type of advanced computer optimization control algorithms based on model prediction.The typical algorithms of model predictive control are model algorithmic control (MAC);dynamic matrix control (DMC);generalized predictive control (GPC).They are both based on three teaches:model prediction;rolling optimization and feedback emendation.The trait of model predictive control is:the mathematic model of controlled system is easy to acquire, and it is not need to complicated system analysis and precise modeling;since rolling optimization based on feedback emendation instead of conventional optimization control,then the controlled system can conquer the uncertainty influence,increasing the robustness and calculating burden on-line is opposite simple.Compared with these three control arithmetic,dynamic matrix control is more convenience and applied,and is easy to get the satisfactory control quality.My work in the paper is to research on the cascade control,which main loop and assistant loop both use dynamic matrix control,and through the computer simulation to approve the theory feasible and advanced.