Constrained generalized predictive control algorithm with PID feedback correction scheme

A generalized predictive control (GPC) algorithm frequently exploits repeated online identification to overcome model mismatch. However, the online identification is adverse to real time situations due to its heavy computational burden. Therefore, a constrained GPC algorithm with a PID feedback correction strategy is proposed in this paper to overcome model-process mismatching. Compared with conventional online identification, this feedback correction strategy not only can greatly reduce the computational burden, but also can effectively overcome the model-process mismatch. A simulation example is given, which illustrates that the presented approach can overcome linear modeling errors near an operating point and nonlinear modeling errors far away from the operating point simultaneously.