Adaptive Cascade Generalized Predictive Control

Abstract

Cascade control is one of the most popular structures for process control as it is a special architecture for dealing with disturbances. However, the drawbacks of cascade control are obvious that primary controller and secondary controller should be tuned together, which influences each other. In this paper, a new Adaptive Cascade Generalized Predictive Controller (ACGPC) is introduced. ACGPC is a method issued from GPC and the inner and outer controllers of a cascade system are replaced by one cascade generalized predictive controller, where both loops model are updated by Recursive Least Squares method. Compared with existing methods, the new method is simpler and yet more effective. It can be directly integrated into commercially available industrial auto-tuning systems. Some examples are given to illustrate the effectiveness and robustness of the proposed method.

Universal phase shifter regulator system modeling with robust GPC using neural networks for compensation power in transmission line

“…The principle of GPC owes its name to the fact that it takes into account predictions of process's future outputs and sometimes also of the future inputs [9]- [11]. The outputs and the inputs are predicted over a finite horizon, then on the synthesis of a control system capable of anticipating setpoint variations.…”