中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An effcient iterative approach for dynamic output feedback robust model predictive control

文献类型:会议论文

作者Yang, Yuanqing4; Zou T(邹涛)2; Ping, Xubin1; Hu, Jianchen4; Ding, Baocang4; Wang, Yong4; Zhao, Jun3; Xu, Zuhua3
出版日期2019
会议日期June 9-12, 2019
会议地点Kitakyushu-shi, Japan
页码1283-1288
英文摘要The problem of dynamic output feedback robust model predictive control (MPC) for linear parameter varying (LPV) system with bounded disturbance is addressed. In the previous approaches, an inner iteration loop handles the mutual inverse Lyapunov matrices by applying the cone complementary approach, and an outer iteration loop minimizes the performance cost by iterating the inner loop. By utilizing a linearization method to handle the mutual inverse Lyapunov matrices, the new approach in this paper utilizes a single iteration loop to replace the double iteration loops in the previous approach, so that the computational burden can be greatly reduced. The recursive feasibility and closed-loop stability are guaranteed. A numerical example is given to illustrate the effectiveness of the proposed approach.
源文献作者City of Kitakyushu ; Kakenhi ; Kitakyushu Convention and Visitors Association
产权排序2
会议录2019 12th Asian Control Conference, ASCC 2019
会议录出版者IEEE
会议录出版地New York
语种英语
ISBN号978-4-88898-300-6
WOS记录号WOS:000490720700224
源URL[http://ir.sia.cn/handle/173321/25390]  
专题沈阳自动化研究所_工业控制网络与系统研究室
通讯作者Ding, Baocang
作者单位1.School of Electro-Mechanical Engineering, Xidian University, Xi'an 710071, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.National Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
4.Department of Automation, School of Electronic and Information Engineering, Xi'An Jiaotong University, Xi'an 710049, China
推荐引用方式
GB/T 7714
Yang, Yuanqing,Zou T,Ping, Xubin,et al. An effcient iterative approach for dynamic output feedback robust model predictive control[C]. 见:. Kitakyushu-shi, Japan. June 9-12, 2019.

入库方式: OAI收割

来源:沈阳自动化研究所

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