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Output-feedback control of nonlinear systems using direct adaptive fuzzy-neural controller

机译:使用直接自适应模糊神经控制器的非线性系统的输出反馈控制

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摘要

In this paper, a direct adaptive fuzzy-neural output-feedback controller (DAFOC) for a class of uncertain nonlinear systems is developed under the constraint that only the system output is available for measurement. An output feedback control law and an update law are derived for on-line tuning the weighting factors of the DAFOC. By using strictly positive-real Lyapunov theory, the stability of the closed-loop system compensated by the DAFOC can be verified. Moreover, the proposed overall control scheme guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.
机译:本文针对一类不确定的非线性系统,在仅系统输出可用于测量的约束下,开发了一种直接自适应模糊神经输出反馈控制器(DAFOC)。导出了输出反馈控制律和更新律,以在线调整DAFOC的加权因子。通过使用严格的正实Lyapunov理论,可以验证由DAFOC补偿的闭环系统的稳定性。此外,所提出的总体控制方案保证了所涉及的所有信号都受到限制,并且闭环系统的输出渐近跟踪所需的输出轨迹。为了证明该方法的有效性,本文给出了仿真结果。

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