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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
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
作者姓名:张友安  陈善本  周绍磊  杨 涤
作者单位:1. 海军航空工程学院301教研室·烟台,264001
2. 哈尔滨工业大学现代焊接生产技术国家重点实验室·哈尔滨,150001
3. 哈尔滨工业大学航天工程与力学系·哈尔滨,150001
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笥化的未知的非线性动态系统儿得要求的患 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)。

关 键 词:MIMO 非线性系统 反馈线性化 模糊CMA 神经网络
收稿时间:1997-10-28
修稿时间:1997-10-28

Fuzzy CMAC Neural Networks Based Feedback Linearization for MIMO Nonlinear Systems
ZHANG You-an,CHEN Shan-ben,ZHOU Shao-lei and YANG Di. Fuzzy CMAC Neural Networks Based Feedback Linearization for MIMO Nonlinear Systems[J]. Control Theory & Applications, 2000, 17(1): 107-109
Authors:ZHANG You-an  CHEN Shan-ben  ZHOU Shao-lei  YANG Di
Affiliation:Naval Aeronautical Engineering College, Yantai,264001,P.R.China;National Key Laboratory of Advanced Welding Production Technology,Harbin Institute of Technology, Harbin,150001,P.R.China;Naval Aeronautical Engineering College, Yantai,264001,P.R.China;Department of Austranautics and Mechanics,Harbin Institute of Technology, Harbirn,150001,P.R.China
Abstract:A fuzzy CMACneural network based controller that feedback-linearizes a class of state-feedbacklinearizable MIMO continuous-time nonlinear systems with state space affine form ispresented. The control action is used to achieve the desired tracking performance. Astability proof is given strictly in the sense of Lyapunov. It is shown that all thesignals in the closed loop system are uniformly ultimately bounded.
Keywords:MIMO nonlinear systems  feedback linearization  fuzzy CMAC neural networks
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