Model predictive control of open-loop unstable cascade systems

In this paper we develop a novel state estimation-based model predictive control approach that has the same general philosophy of cascade control (taking advantage of secondary measurements to aid disturbance rejection). The model predictive control formulation can be applied to open-loop unstable cascade systems and has the additional advantage of being able to explicitly handle constraints. Traditional cascade control strategies are designed for open-loop stable systems, and there is no set procedure to tune cascade controllers for these systems. The example application is a jacketed exothermic chemical reactor, where jacket temperature is used as a secondary measurement in order to infer disturbances in jacket feed temperature and/or reactor feed flow rate. The MPC-based cascade strategy yields significantly better performance than classical cascade control when operating close to constraints on the jacket flow rate