In this work, we propose a robust cooperative distributed MPC based on a multi-model approach. A new method for obtaining a state-space model in the velocity-form of inputs is presented. This model is suitable for predicting steady-state outputs within an offset-free setpoint tracking framework in which a terminal constraint is relaxed to guarantee problem feasibility under any setpoint change. The proposed strategy also deals with the zone control problem, which is widely applied in the process industry. Moreover, an alternative algorithm is proposed in order to improve convergence over iterations. Recursive feasibility, convergence and stability properties are proved. Two numerical examples are provided with the application of the proposed algorithms.

在这项工作中，我们提出了一种基于多模型方法的强大的协作分布式 MPC。提出了一种获得输入速度形式的状态空间模型的新方法。该模型适用于在无偏移设定点跟踪框架内预测稳态输出，其中放宽终端约束以保证在任何设定点变化下问题的可行性。所提出的策略还解决了在过程工业中广泛应用的区域控制问题。此外，提出了一种替代算法，以提高迭代的收敛性。证明了递归的可行性、收敛性和稳定性。提出的算法的应用提供了两个数值示例。