Networked distributed model predictive control for multi-variable coupling process

Networked Distributed Model Predictive Control (NDMPC) is an effective control strategy which is usually used to control large-scale industrial processes with multi-variable coupling. However, data transmission and information exchange are carried out through the network in this control system, it will inevitably appear the phenomenon of network time-varying delay and data packet dropout, which will lead to the overall performance and stability of the system. How to design a networked controller that can satisfy the optimization control of the subsystem and meet the constraint conditions are the key. In this paper, combined with the networked model predictive control strategy with a comparison process based on coordination, to compensate for time-varying delays in communication between subsystems. As a study case, an overall integrated plant which composes of two-unit connected via other processes and intermediate tanks under severe constraints is used to demonstrate the effectiveness and usability of this framework.