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基于观测器的未知非线性动态系统自适应模糊神经控制

Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems.

作者信息

Leu Y G, Lee T T, Wang W Y

机构信息

Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei.

出版信息

IEEE Trans Syst Man Cybern B Cybern. 1999;29(5):583-91. doi: 10.1109/3477.790441.

Abstract

In this paper, an observer-based adaptive fuzzy-neural controller for a class of unknown nonlinear dynamical systems is developed. The observer-based output feedback control law and update law to tune on-line the weighting factors of the adaptive fuzzy-neural controller are derived. The total states of the nonlinear system are not assumed to be available for measurement. Also, the unknown nonlinearities of the nonlinear dynamical systems are not restricted to the system output only. The overall adaptive scheme guarantees that all signals involved are bounded. Simulation results demonstrate the applicability of the proposed method in order to achieve desired performance.

摘要

本文针对一类未知非线性动态系统,设计了一种基于观测器的自适应模糊神经控制器。推导了基于观测器的输出反馈控制律和用于在线调整自适应模糊神经控制器加权因子的更新律。假设非线性系统的所有状态不可用于测量。此外,非线性动态系统的未知非线性项并不局限于系统输出。整体自适应方案保证了所有相关信号均有界。仿真结果证明了所提方法在实现期望性能方面的适用性。

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