This work focuses on the design of stochastic Lyapunov‐based economic model predictive control (SLEMPC) systems for a broad class of stochastic nonlinear systems with input constraints. Under the assumption of stabilizability of the origin of the stochastic nonlinear system via a stochastic Lyapunov‐based control law, an economic model predictive controller is proposed that utilizes suitable constraints based on the stochastic Lyapunov‐based controller to ensure economic optimality, feasibility and stability in probability in a well‐characterized region of the state‐space surrounding the origin. A chemical process example is used to illustrate the application of the approach and demonstrate its economic benefits with respect to an EMPC scheme that treats the disturbances in a deterministic, bounded manner. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3312–3322, 2018

中文翻译：

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随机非线性系统的经济模型预测控制

这项工作的重点是为具有输入约束的一类广泛的随机非线性系统设计基于Lyapunov的随机经济模型预测控制（SLEMPC）系统。在通过基于随机Lyapunov的控制律使随机非线性系统的原点具有可稳定性的假设下，提出了一种经济模型预测控制器，该模型利用基于基于Lyapunov的随机控制器的适当约束来确保经济最优性，可行性和稳定性。围绕原点的状态空间中一个特征明确的区域中的概率。使用化学过程示例来说明该方法的应用，并证明该方法相对于以确定性，有界的方式处理干扰的EMPC方案而言，具有经济效益。AIChE J，64：3312–3322，2018