Responsive Economic Model Predictive Control for Next-Generation Manufacturing
Responsive Economic Model Predictive Control for Next-Generation Manufacturing
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DOI：
10.3390/math8020259
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发表时间：
2020-02
期刊：
影响因子：
2.4
通讯作者：
Helen Durand
中科院分区：
文献类型：
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作者：
Helen Durand
越来越多的人希望自动化系统能够执行人类执行的任务，例如驾驶，语音识别和异常检测。因此，自动化系统越来越需要对意外情况做出响应。在化学过程工业中，两种类型的相关意外条件是异常条件和操作员和工程师对控制器行为的响应。增强称为经济模型预测控制（EMPC）的先进控制设计的响应性（其使用对未来过程行为的预测来确定操作过程的经济上最优的方式）这些类型的意外条件将推动这种控制器向人工智能属性的转变，超越它今天所拥有的，并将为这种控制器的可解释性和验证提供新的思路。controller.这项工作提供了理论研究，涉及到非线性系统的考虑EMPC这些更高层次的概念，使用两个想法EMPC配方的动机有关的控制设计的自我修改后，人类的感知过程响应的具体情况下，收到和控制器处理异常。
There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected conditions. Two types of unexpected conditions of relevance in the chemical process industries are anomalous conditions and the responses of operators and engineers to controller behavior. Enhancing responsiveness of an advanced control design known as economic model predictive control (EMPC) (which uses predictions of future process behavior to determine an economically optimal manner in which to operate a process) to unexpected conditions of these types would advance the move toward artificial intelligence properties for this controller beyond those which it has today and would provide new thoughts on interpretability and verification for the controller. This work provides theoretical studies which relate nonlinear systems considerations for EMPC to these higher-level concepts using two ideas for EMPC formulations motivated by specific situations related to self-modification of a control design after human perceptions of the process response are received and to controller handling of anomalies.