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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique
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Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique

机译：一类纯反馈非线性系统的动态表面自适应神经控制

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摘要

This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid “the explosion of complexity” in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method.
机译：本简介解决了一类纯仿射系统的自适应控制问题，这些仿射函数具有非仿射函数可能是不可微的。在不使用平均值定理的情况下，通过对非仿射函数进行适当建模，可以克服纯反馈系统控制设计的困难。借助神经网络逼近器，通过结合动态表面控制（DSC）和最小学习参数（MLP）技术开发了自适应神经控制器。我们方法的关键特征是，首先，消除了对非仿射函数偏导数的限制性假设；其次，在后推设计中使用了DSC技术来避免“复杂性激增”，以及自适应参数的数量使用MLP技术可以显着降低噪声，第三，采用平滑的鲁棒补偿器来规避近似误差和干扰的影响。此外，证明了闭环系统中的所有信号都是半全局一致最终有界的。最后，仿真结果证明了所设计方法的有效性。

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  • 作者

    Zongcheng Liu; Xinmin Dong; Jianping Xue; Hongbo Li; Yong Chen;

  • 作者单位

    Department of Flight control and Electrical Engineering, College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an, China;

    Department of Flight control and Electrical Engineering, College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an, China;

    Department of Flight control and Electrical Engineering, College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an, China;

    Department of Flight control and Electrical Engineering, College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an, China;

    Department of Flight control and Electrical Engineering, College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an, China;

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  • 正文语种 eng
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  • 关键词

    Nonlinear systems; Adaptive systems; Backstepping; Bismuth; Approximation methods; Learning systems; Control design;

    机译：非线性系统自适应系统Backstepping铋近似方法学习系统控制设计;

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