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Adaptive Dynamic Surface Output-Feedback Control for a Class of Hysteric Nonlinear Systems with Prespeeified Tracking Performance

机译:具有滞后跟踪性能的一类滞后非线性系统的自适应动态表面输出反馈控制

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In this paper, a high-gain observer based adaptive dynamic surface output-feedback control is proposed for a class of nonlinear systems preceded by unknown backlash-like hysteresis. The main features are 1) the RBF neural networks are employed to approximate the unknown smooth functions; 2) by using the proposed control scheme and the tracking error transformation functions, the tracking performance could be prespecified; 3) the derivative-explosion problem when the hysteresis is fused with backstepping design can be eliminated, which greatly simplifies the control law; 4) by combining with the estimation of vector norm of the unknown parameters, the computational burden is greatly reduced. Simulation results show the effectiveness of the proposed scheme.
机译:在本文中,针对一类带有未知反冲样磁滞的非线性系统,提出了一种基于高增益观测器的自适应动态表面输出反馈控制。主要特征是:1)采用RBF神经网络对未知的平滑函数进行近似; 2)通过使用所提出的控制方案和跟踪误差变换功能,可以预先指定跟踪性能; 3)消除了滞后与反推设计融合时的导数爆炸问题,大大简化了控制规律。 4)结合未知参数向量范数的估计,大大减轻了计算量。仿真结果表明了该方案的有效性。

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