A stair-like hierarchical predictive control strategy

Model predictive control (MPC) is to solve an optimization problem for a finite future at current time and to implement the first optimal control input as the current control input. To improve the performance of the Stirred Tank Reactor, a new method based on predictive hierarchical control was introduced. As a modification of the regulatory controller usually implies higher costs, it is a common practice in the industry to add a supervisory level instead. The supervisory level dynamically optimizes a general objective function to determine the optimal set-point for a given regulatory level. According to the complexity of online computation, a hierarchical predictive scheme based on stair-like control was proposed. It approximated the future set-point sequences by a set of stair-like controllers per sampling time. The method decreased dimensions of the variables, so it could greatly reduce the online computation burden and prevent the frequent oscillation of the input. Simulation results prove the effectiveness of the proposed controller.