This article proposes a two-layer framework to maximize economic performance through dynamic process economics optimization while addressing fluctuating real-world economics and enhancing cyberattack resilience via encryption in the feedback control layer for nonlinear processes. The upper layer employs a Lyapunov-based economic model predictive control scheme, receiving updated economic information for each operating period, while the lower layer utilizes an encrypted linear feedback control system. Encrypted state information is decrypted in the upper layer to determine the economically optimal dynamic operating trajectory through nonlinear optimization. Conversely, the lower layer securely tracks this trajectory in an encrypted space without decryption. To mitigate the cyber vulnerability of the upper layer, we integrate a cyberattack detector that utilizes sensor-derived data for attack detection. We quantify the errors stemming from quantization, disturbances, and sample-and-hold controller implementation. Simulation results of a nonlinear chemical process highlight the robustness and economic benefits of this new control architecture.

中文翻译：

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集成动态经济优化和加密控制，实现非线性过程的网络弹性运行


本文提出了一个两层框架，通过动态过程经济优化来最大化经济绩效，同时解决现实世界经济波动的问题，并通过非线性过程反馈控制层中的加密来增强网络攻击弹性。上层采用基于李亚普诺夫的经济模型预测控制方案，接收每个运行周期的更新经济信息，而下层采用加密的线性反馈控制系统。加密的状态信息在上层被解密，通过非线性优化确定经济最优的动态运行轨迹。相反，下层在加密空间中安全地跟踪该轨迹而无需解密。为了减轻上层的网络漏洞，我们集成了一个网络攻击检测器，利用传感器衍生的数据进行攻击检测。我们量化由量化、干扰和采样保持控制器实现产生的误差。非线性化学过程的仿真结果凸显了这种新控制架构的稳健性和经济效益。