计算机科学
前馈
控制(管理)
过程控制
解耦(概率)
控制工程
控制系统
级联
模型预测控制
过程(计算)
先进过程控制
简单(哲学)
工业工程
工程类
人工智能
哲学
电气工程
操作系统
认识论
化学工程
标识
DOI:10.1016/j.arcontrol.2023.100903
摘要
The paper explores the standard advanced control elements commonly used in industry for designing advanced control systems. These elements include cascade, ratio, feedforward, decoupling, selectors, split range, and more, collectively referred to as "advanced regulatory control" (ARC). Numerous examples are provided, with a particular focus on process control. The paper emphasizes the shortcomings of model-based optimization methods, such as model predictive control (MPC), and challenges the view that MPC can solve all control problems, while ARC solutions are outdated, ad-hoc and difficult to understand. On the contrary, decomposing the control systems into simple ARC elements is very powerful and allows for designing control systems for complex processes with only limited information. With the knowledge of the control elements presented in the paper, readers should be able to understand most industrial ARC solutions and propose alternatives and improvements. Furthermore, the paper calls for the academic community to enhance the teaching of ARC methods and prioritize research efforts in developing theory and improving design method.
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