In this article, a robust distributed economic model predictive control (DEMPC) approach is developed for plant-wide chemical processes. The proposed approach achieves arbitrary feasible setpoints that may vary frequently, attenuates the plant-wide effects of unknown disturbances and minimizes a plant-wide economic cost. In this approach, a plant-wide process is represented as a network of process units and each process unit is controlled by an individual controller which shares a plant-wide optimization economic objective and stability conditions through the network. To ensure the convergence of process variables to arbitrary setpoints, a contraction condition is developed for the DEMPC, based on the contraction theory. To deal with the effects of interactions among process units, the concept of dissipativity is adopted. Using sum-separable control contraction metrics, a reference-independent robust stability condition is developed to ensure the plant-wide disturbance effects (under interactions among process units) to be attenuated in terms of differential ℒ₂ gain and represented by a plant-wide differential dissipativity condition, which is converted into the differential dissipativity conditions that individual controllers need to satisfy. This approach facilitates the optimization of plant-wide economic costs with global constraints in a distributed way, allowing efficient implementation of alternating direction method of multipliers (ADMM). The proposed approach is illustrated using a reactor-separator process.

中文翻译：

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基于微分耗散的鲁棒分布经济模型预测控制

在本文中，为整个工厂的化学过程开发了一种可靠的分布式经济模型预测控制（DEMPC）方法。所提出的方法实现了可能经常变化的任意可行的设定点，减弱了未知干扰对整个工厂的影响，并使整个工厂的经济成本降至最低。在这种方法中，将整个工厂范围的过程表示为过程单元的网络，并且每个过程单元都由单独的控制器控制，该控制器通过网络共享整个工厂范围内的优化经济目标和稳定性条件。为了确保过程变量收敛到任意设定值，基于收缩理论为DEMPC开发了收缩条件。为了处理过程单元之间的交互作用，采用了耗散性概念。gain ₂增益，由工厂范围内的微分耗散条件表示，该条件转换为单个控制器需要满足的微分耗散条件。这种方法有助于以全局方式以分布式方式优化全厂范围的经济成本，从而可以有效地实现乘数的交替方向法（ADMM）。使用反应器-分离器工艺说明了所提出的方法。