科研成果详情

题名Robust PI controller design for nonlinear systems via fuzzy modelling approach
作者
发表日期2001
会议名称40th IEEE Conference on Decision and Control (CDC)
会议录名称Proceedings of the IEEE Conference on Decision and Control
ISBN0780370619
ISSN0191-2216
卷号5
页码4346-4351
会议日期4 December 2001 through 7 December 2001
会议地点Orlando, FL, USA
摘要

The design problem of proportional and proportional-plus-integral (PI) controllers for nonlinear systems is studied in this paper. First, Takagi-Sugeno fuzzy model with parameter uncertainties is used to approximate the nonlinear systems. Then a numerically tractable algorithm based on the technique of iterative linear matrix inequalities is developed to design a proportional (static output feedback) controller for the robust stabilization of the system in Takagi-Sugeno fuzzy model. Thirdly, we transform the problem of PI controller design to that of proportional controller design for an augmented system and thus bring the solution of the former problem into the configuration of the developed algorithm. Finally, the proposed method is applied to the design of robust stabilizing controllers for the excitation control of power systems. Simulation results show that the transient stability can be improved by using a fuzzy PI controller when large faults appear in the system, compared to the conventional PI controller designed by using linearization method around the steady state.

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收录类别CPCI-S
语种英语English
WOS研究方向Automation & Control Systems ; Computer Science ; Engineering ; Operations Research & Management Science
WOS类目Automation & Control Systems ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号WOS:000178362200800
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/4388
专题个人在本单位外知识产出
作者单位
Dept. of Elec. and Comp. Engineering, National University of Singapore, Singapore 119260, Singapore
推荐引用方式
GB/T 7714
Zheng, Feng,Wang, Qingguo,Lee, Tong Henget al. Robust PI controller design for nonlinear systems via fuzzy modelling approach[C], 2001: 4346-4351.
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