| 基于神经网络非线性系统辨识和控制的研究 |
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| 引用本文： | 任雪梅,高为炳.基于神经网络非线性系统辨识和控制的研究[J].控制理论与应用,1995,12(2):147-153. |
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| 作者姓名： | 任雪梅 高为炳 |
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| 作者单位： | 北京航空航天大学第七研究室 |
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| 摘 要： | 本文提出了由静态的前馈网络和稳定的滤波器构成的非线性系统的辨识模型，在神经网络固有的逼近误差存在的情况下，从理论上讨论了神经网络应用于辨识控制过程中系统的稳定性问题，最后研究了在非线性系统的轨迹跟踪过程中增加滑动控制来偿神经网络的逼近误差，从而提高系统跟踪性能。
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| 关 键 词： | 神经网络 非线性系统 辨识 滑动控制 |
| 收稿时间： | 1994/1/27 0:00:00 |
| 修稿时间： | 1994/5/18 0:00:00 |
Identification and Control of Nonlinear Systems Using Neural Networks |
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| REN Xuemei and GAO Weibing.Identification and Control of Nonlinear Systems Using Neural Networks[J].Control Theory & Applications,1995,12(2):147-153. |
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| Authors: | REN Xuemei and GAO Weibing |
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| Affiliation: | The seventh Research Division, Beijing University of Aeronautics and Astronautics |
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| Abstract: | In this paper we present an identification model constructed by static feedforward neural networks and stable filters for nonlinear dynamical systems.Adaptive identification and control schemes based on neural networks are shown to guarantee stability of the system, even in the presence of neural network approximation errors. Finally, sliding control is used to compensate for inherent network approximation errors in order to improve the tracking performance. |
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| Keywords: | neural networks nonlinear systems identification sliding control |
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