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Teaching Industrial Internet-of-Things-Based Model-Predictive Controller
IEEE Transactions on Education ( IF 2.6 ) Pub Date : 2020-12-09 , DOI: 10.1109/te.2020.3037370
N. Muthukumar , Seshadhri Srinivasan , B. Subathra , K. Ramkumar

Contribution: This article explores how the Industrial Internet of Things (IIoT) could be leveraged to enhance the teaching/learning experience of advanced control techniques [e.g., model-predictive control (MPC)] for complex systems (nonlinear and multivariable) for undergraduate students. Background: The IIoTs’ features, such as ubiquitous sensing, open connectivity, and distributed control, are expected to transform the way control is implemented in the industries. The students need to be prepared for this development. Courses on advanced control techniques should be revamped considering this change. In particular, deploying advanced controllers in IIoT scenarios could make the students ready for Industrie 4.0 and enhance the teaching-learning experience. Intended Outcomes: To reduce the cost for setting up laboratories; to make students appreciate IIoT benefits in industries and study the enhancements in teaching/learning advanced control techniques, such as MPC. The focus is on implementing MPC for a complex process, i.e., nonlinear, multivariable, and having interactions and their deployment on IIoT hardware. Method: A ten-day course on IIoTs’ benefits and implementing advanced control techniques for a complex process with lecturing and hands-on sessions for undergraduate students is used. The course focuses on understanding basic concepts to deploy advanced control techniques on IIoT hardware in industries. Findings: The learning experience is enthralling, and the students are appreciative of the IIoT benefits to the industries and in their learning experience, which is demonstrated by their in-depth understanding of concepts on system complexity and implementing MPC.

中文翻译:

基于工业物联网的模型预测控制器教学

贡献:本文探讨了如何利用工业物联网 (IIoT) 来增强本科生复杂系统(非线性和多变量)的高级控制技术 [例如模型预测控制 (MPC)] 的教学/学习体验. 背景:IIoT 的泛在传感、开放连接和分布式控制等特性有望改变行业控制的实施方式。学生需要为这种发展做好准备。考虑到这一变化,应改进高级控制技术课程。特别是,在工业物联网场景中部署高级控制器可以让学生为工业 4.0 做好准备,提升教学体验。预期成果:降低建立实验室的成本;使学生了解工业物联网的优势,并研究教学/学习高级控制技术(如 MPC)的改进。重点是为复杂的过程实施 MPC,即非线性、多变量以及在 IIoT 硬件上进行交互和部署。方法:使用为期 10 天的课程,内容涉及 IIoT 的优势以及为复杂过程实施高级控制技术,为本科生提供讲座和实践课程。本课程侧重于了解在工业 IIoT 硬件上部署高级控制技术的基本概念。发现:学习体验令人着迷,学生们对 IIoT 给行业和他们的学习体验带来的好处表示赞赏,他们对系统复杂性和实施 MPC 的概念的深入理解证明了这一点。
更新日期:2020-12-09
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