Assessment and comparison of distributed model predictive control schemes: Application to a natural gas refrigeration plant

• Development of a software interface to apply MATLAB-based controllers to DynSim.
• Model realization and design issues are investigated for different DMPC methods.
• Implementation, communication, computation, and practical issues are investigated.
• Simulations are illustrated, showing the performances of different DMPC methods.

A number of decentralized and distributed control schemes based on model predictive control (MPC) have been introduced in the last years. They have been proposed as viable solutions to the computational, transmission and robustness issues arising in the centralized context in case of large-scale and/or distributed plants. Such MPC-based control schemes are very heterogeneous, based on different model structures and realizations, with different features and infrastructural/memory/computational requirements.In this paper, we test and compare, with a realistic case study, a robust non-cooperative scheme and a cooperative iterative one. The main scope is to analyze and unravel, in a fair comparison scenario, these methods from different viewpoints, spanning from the model realization issues to the communication and computational requirements, to the control performances. The benchmark case study consists of an existing natural gas refrigeration plant. Realistic simulations and validation tests are obtained through in the DynSim industrial process simulation environment.