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Adaptive Neural Network Control for a Class of Uncertain Nonlinear Systems with Unknown Control Directions

机译:一类具有未知控制方向的一类不确定非线性系统的自适应神经网络控制

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摘要

A robust adaptive neural network control scheme is proposed for a class of strict-feedback nonlinear systems with unknown control directions and unmodeled dynamics. The proposed design method expands the class of nonlinear systems for which robust adaptive control approaches have been studied. A priori knowledge of the signs of the control directions is not required. It is proved that under the proposed control law, all the closed-loop signals are uniformly ultimately bounded and the output asymptotically converges to zero. Simulation study is provided to verify the theoretical results.
机译:提出了一种坚固的自适应神经网络控制方案,用于一类具有未知控制方向和未拼接动态的严格反馈非线性系统。所提出的设计方法扩展了已经研究了鲁棒自适应控制方法的非线性系统的类别。不需要先验的控制方向迹象知识。证明,在提出的控制法下,所有闭环信号都是均匀的最终界限,输出渐近地会聚到零。提供仿真研究以验证理论结果。

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