论文标题
用于闭环控制系统的AI - 建模，设计和调整控制系统的新机会
AI for Closed-Loop Control Systems -- New Opportunities for Modeling, Designing, and Tuning Control Systems
论文作者
论文摘要
如今，控制系统，尤其是闭环控制系统（CLC），经常用于生产机器，车辆和机器人。需要CLC积极地使过程的实际值与给定参考值或实时设置值相关，并具有很高的进动。然而，人工智能（AI）并未用于建模，设计，优化和调整CLC。本文将重点介绍潜在的AI授权和基于基于的控制系统设计和设计程序，在控制系统工程领域收集新的机会和研究方向。因此，本文说明了CLC的标准框图中哪些构建块可以用AI（即人工神经元网络（ANN））代替。具有实时的流程包含和功能安全性，可以讨论基于AI的控制器块是否可以应对这些需求。通过总结本文，讨论了AI授权以及基于基于AI的CLCS设计的优缺点，并提供了在控制系统工程领域引入AI的可能的研究说明。
Control Systems, particularly closed-loop control systems (CLCS), are frequently used in production machines, vehicles, and robots nowadays. CLCS are needed to actively align actual values of a process to a given reference or set values in real-time with a very high precession. Yet, artificial intelligence (AI) is not used to model, design, optimize, and tune CLCS. This paper will highlight potential AI-empowered and -based control system designs and designing procedures, gathering new opportunities and research direction in the field of control system engineering. Therefore, this paper illustrates which building blocks within the standard block diagram of CLCS can be replaced by AI, i.e., artificial neuronal networks (ANN). Having processes with real-time contains and functional safety in mind, it is discussed if AI-based controller blocks can cope with these demands. By concluding the paper, the pros and cons of AI-empowered as well as -based CLCS designs are discussed, and possible research directions for introducing AI in the domain of control system engineering are given.
