Distributed model predictive control based on dissipativity


Correspondence concerning this article should be addressed to J. Bao at j.bao@unsw.edu.au.


A noncooperative approach to plant-wide distributed model predictive control based on dissipativity conditions is developed. The plant-wide process and distributed control system are represented as two interacting process and controller networks, with interaction effects captured by the dissipativity properties of subsystems and network topologies. The plant-wide stability and performance conditions are developed based on global dissipativity conditions, which in turn are translated into the dissipative trajectory conditions that each local model predictive control MPC must satisfy. This approach is enabled by the use of dynamic supply rates in quadratic difference forms, which capture detailed dynamic system information. A case study is presented to illustrate the results. © 2012 American Institute of Chemical Engineers AIChE J, 59: 787–804, 2013