智能控制课程中PID控制器参数的智能优化教学实验设计  

Experimental Design of Intelligent Optimization for PID Controller Parameters Tuning in Intelligent Control Course

作　　者：陈帆 潘天红 张德祥[1] CHEN Fan;PAN Tianhong;ZHANG Dexiang(School of Electrical Engineering and Automation,Anhui University,Hefei,Anhui 230601,China)

机构地区：[1]安徽大学电气工程与自动化学院,安徽合肥230601

出　　处：《自动化应用》2023年第12期27-29,34,共4页Automation Application

基　　金：安徽省线下精品课程项目(2020kfkc031)。

摘　　要：本文主要研究“智能控制”课程的实验教学,在PID控制器参数智能优化的实验教学环节中引入灰狼算法。首先,介绍了该课程涉及的知识点,以及其对自动化专业学生毕业要求指标点的支撑作用。其次,阐述了灰狼算法这种群智能优化算法的算法原理、算法流程等相关理论知识,并着重描述基于灰狼算法的PID控制器优化设计的实验案例。实践结果表明,该方法能显著提高学生对“智能控制”课程的学习效果,充分调动学生的学习主动性,培养学生的团队协作能力和解决复杂工程问题的能力。The experimental teaching of “intelligent control” is investigated in this paper,especially for PID controller parameters tuning using Gray Wolf Optimization(GWO) algorithm.Firstly,the contents of course,including the knowledge points,and the supporting roles of graduation requirements for students from the major of automation.Then,the principle,calculating process and other related theoretical knowledge of GWO are introduced.In particular,the experimental case of PID controller optimization design using GWO is investigated.The applying results show that the presented method significantly improves the students′ learning interests in “intelligent control” course,cultivate students′ collaboration ability,and promote the capability to solve complex engineering problems.

关 键 词：智能控制 灰狼算法 实验教学 优化设计 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]