| 引用本文: | 裴海龙，周其节.基于神经网络的非线性系统近似线性化[J].控制理论与应用,1998,15(1):31~38.[点击复制] |
| PEIHailong and ZHOU Qijie.Approximate Linearization of Nonlinear Systems A Neural Network Approach*[J].Control Theory & Applications,1998,15(1):31~38.[点击复制] |
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| 基于神经网络的非线性系统近似线性化 |
| Approximate Linearization of Nonlinear Systems A Neural Network Approach* |
| 摘要点击 1320 全文点击 633 投稿时间：1996-04-15 修订日期：1997-04-04 |
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| DOI编号 |
| 1998,15(1):31-38 |
| 中文关键词 神经网络 近似线性化 |
| 英文关键词 neural networks approximation linearization |
| 基金项目 |
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| 中文摘要 |
| 神经网络具有同时逼近某一函数及其高阶导数的功能， 这一结果为神经网络在非线性系统中的应用提供了可行的工具， 本文提出了一种利用网络近似功能的非线性系统的近似线性化方法， 无论系统是否满足可积条件， 神经网络都可实现其对合条件的近似积分， 从而构造满足系统近似线性化的反馈控制. 对球一杆系统的仿真结果显示了这种方法的有效性， |
| 英文摘要 |
| Recent researches show that neural networks have the ablilty to approximate a function as well as its derivatives. This result offers a promising opportunity to introduce neural network theory into nonlinear system control. In this paper a novel method of approximate nonlin-ear svstem linearization with neural networks is proposed. The network approximator is designed to integrate the involutive equation of a nonlinear system whether the integrability condition is satisfied or not. Simulation results show that this method is feasible. |