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个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职：Professor at the Institute of Advanced Measurement & Control Technology
其他任职：先进检测与控制技术研究所所长
性别：男
毕业院校：上海交通大学
学位：博士
所在单位：控制科学与工程学院
学科：控制理论与控制工程. 化学工程
办公地点：大连理工大学控制科学与工程学院先进检测与控制技术研究所
大连市凌工路2号大连理工大学海山楼A座724室
联系方式：Tel:(0411)84706465 实验室网站：http://act.dlut.edu.cn/
电子邮箱：tliu@dlut.edu.cn
Indirect iterative learning control design based on 2DOF IMC for batch processes with input delay
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论文类型：会议论文
发表时间：2017-01-01
收录刊物：EI、CPCI-S、Scopus
页面范围：3587-3592
关键字：Batch processes; input delay; two-degree-of-freedom control (2DOF); internal model control (IMC); iterative learning control (ILC); convergence
摘要：In this paper, an indirect type iterative learning control (ILC) scheme is proposed for industrial batch processes with input delay, based on using a two-degree-of-freedom control (2DOF) internal model control (IMC) structure. An important merit is that the 2DOF IMC design for robust closed-loop control against process uncertainties and load disturbance is independent of the ILC design specifically for set-point tracking. To realize prefect tracking, an ILC controller in the form of proportional-derivative (PD) is proposed for the convenience of implementation. There is a single adjustable parameter in the proposed ILC controller, which may be monotonically tuned to meet a good trade-off between the tracking performance and its robustness against process uncertainties. Sufficient conditions to guarantee the convergence of ILC are derived. An illustrative example is used to demonstrate the effectiveness and merit of the proposed ILC method.