Sparse-identification-based model predictive control of nonlinear two-time-scale processes
Sparse-identification-based model predictive control of nonlinear two-time-scale processes
复制标题
基于稀疏辨识的非线性二时间尺度过程模型预测控制
DOI：
10.1016/j.compchemeng.2021.107411
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
P. Christofides
中科院分区：
文献类型：
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作者：
Fahim Abdullah;Zhe Wu;P. Christofides
本文研究了仅利用过程测量数据的非线性双时间尺度过程模型预测控制器的设计。首先识别并隔离双时间尺度过程中的慢变量和快变量，基于仅由慢变量组成的精简慢子系统设计模型预测控制器，因为当快速状态直接包含在控制器所使用的模型中时，会降低控制器的性能。与早期的工作相比，在本工作中，减少的慢子系统是使用稀疏识别从过程数据构建的，它使用高效的凸算法将非线性动态系统识别为一阶常微分方程，该算法具有高度优化和可扩展性。将奇异摄动数学框架的结果与标准假设相结合，得到了完整奇异摄动闭环系统闭环稳定的充分条件。通过将所提出的控制器设计应用于具有不同时间尺度浓度和温度变化曲线的非等温反应器，证明了该控制器设计的有效性，其中发现基于稀疏识别的慢子系统的控制器与现有方法相比，在相同的控制器参数下可以实现更好的闭环性能。
This paper focuses on the design of model predictive controllers for nonlinear two-time-scale processes using only process measurement data. By first identifying and isolating the slow and fast variables in a two-time-scale process, the model predictive controller is designed based on the reduced slow subsystem consisting of only the slow variables, since the fast states can deteriorate controller performance when directly included in the model used in the controller. In contrast to earlier works, in the present work, the reduced slow subsystem is constructed from process data using sparse identification, which identifies nonlinear dynamical systems as first-order ordinary differential equations using an efficient, convex algorithm that is highly optimized and scalable. Results from the mathematical framework of singular perturbations are combined with standard assumptions to derive sufficient conditions for closed-loop stability of the full singularly perturbed closed-loop system. The effectiveness of the proposed controller design is illustrated via its application to a non-isothermal reactor with the concentration and temperature profiles evolving in different time-scales, where it is found that the controller based on the sparse identified slow subsystem can achieve superior closed-loop performanceversusexisting approaches for the same controller parameters.