引用本文: | 张友安,陈善本,周绍磊,杨 涤.模糊CMAC神经网络用于MIMO非线性系统的反馈线性化[J].控制理论与应用,2000,17(1):107~109.[点击复制] |
ZHANG You-an,CHEN Shan-ben,ZHOU Shao-lei,YANG Di.Fuzzy CMAC Neural Networks Based Feedback Linearization for MIMO Nonlinear Systems[J].Control Theory and Technology,2000,17(1):107~109.[点击复制] |
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模糊CMAC神经网络用于MIMO非线性系统的反馈线性化 |
Fuzzy CMAC Neural Networks Based Feedback Linearization for MIMO Nonlinear Systems |
摘要点击 1358 全文点击 818 投稿时间:1997-10-28 修订日期:1999-02-01 |
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DOI编号 10.7641/j.issn.1000-8152.2000.1.026 |
2000,17(1):107-109 |
中文关键词 MIMO非线性系统 反馈线性化 模糊CMAC神经网络 |
英文关键词 MIMO nonlinear systems feedback linearization fuzzy CMAC neural networks |
基金项目 国家自然科学基金(59635160 & 19572114)资助课题. |
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中文摘要 |
针对一类多输入多输出(MIMO)连续时间非线性系统,应用模糊CMAC神经网络,给出一种状态反馈控制器,用于使状态反馈可线性化的未知的非线性动态系统获得要求的跟踪性能.在很弱的假设条件下,应用李雅普诺夫稳定性理论严格地证明了闭环系统内的所有信号为一致最终有界(UUB). |
英文摘要 |
A fuzzy CMAC neural network based controller that feedback linearizes a class of state feedback linearizable MIMO continuous time nonlinear systems with state space affine form is presented. The control action is used to achieve the desired tracking performance. A stability proof is given strictly in the sense of Lyapunov. It is shown that all the signals in the closed loop system are uniformly ultimately bounded. |