使用 Takagi-Sugeno 模糊模型的非线性动态定位船的改进型采样数据控制。

IF 2.6 4区 工程技术 Q1 Mathematics
Minjie Zheng, Yulai Su, Guoquan Chen
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引用次数: 0

摘要

本文探讨了采用高木-菅野(Takagi-Sugeno,T-S)模糊模型的动态定位船(DPS)的采样数据控制问题。通过引入新的有用项(如时间的二阶项),构建了改进的 Lyapunov-Krasovskii 函数(LKF)。此外,还引入了互凸方法来约束 LKF 的导数。根据所构建的 LKF,整个采样周期内的采样信息得到了充分利用,并获得了较小的保守性。然后,通过线性矩阵不等式(LMI)分析了稳定性条件、鲁棒性能、模式不确定性和采样数据控制器设计。最后,举例说明了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved sampled-data control for a nonlinear dynamic positioning ship with Takagi-Sugeno fuzzy model.

This article considered the sampled-data control issue for a dynamic positioning ship (DPS) with the Takagi-Sugeno (T-S) fuzzy model. By introducing new useful terms such as second-order term of time, an improved Lyapunov-Krasovskii function (LKF) was constructed. Additionally, the reciprocally convex method is introduced to bound the derivative of LKF. According to the constructed LKF, the sampling information during the whole sampling period was fully utilized, and less conservatism was obtained. Then, the stability condition, robust performance, mode uncertainty and sampled-data controller design were analyzed by means of the linear matrix inequality (LMI). Finally, an example was given to demonstrate the effectiveness of the proposed method.

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来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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