| 高斯基神经网络的非线性PID控制方法 |
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| 引用本文： | 曾喆昭,肖雅芬,蒋 杰,朱静涛. 高斯基神经网络的非线性PID控制方法[J]. 计算机工程与应用, 2013, 49(9): 255-258 |
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| 作者姓名： | 曾喆昭 肖雅芬 蒋 杰 朱静涛 |
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| 作者单位： | 1.长沙理工大学 电气与信息工程学院，长沙 4100762.岳阳市电业局，湖南 岳阳 414000 |
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| 摘 要： | 针对二阶非线性系统，提出了一种用高斯基函数作为神经元激励函数的PID（Proportion-Integral-Derivative）控制方法。该方法用高斯基函数模拟PID参数随误差变化的曲线，用神经网络算法在线调整各模拟曲线的系数，从而构造出具有非线性特征的PID控制策略，实现了基于高斯基神经网络的非线性PID智能控制方法。计算机仿真结果表明，该方法具有良好的非线性控制效果，因此在工业领域具有广泛的应用前景。
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| 关 键 词： | 非线性比例-积分-微分（PID） 高斯基神经网络 智能控制 |
Nonlinear PID control method using Gaussian basis neural network |
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| ZENG Zhezhao,XIAO Yafen,JIANG Jie,ZHU Jingtao. Nonlinear PID control method using Gaussian basis neural network[J]. Computer Engineering and Applications, 2013, 49(9): 255-258 |
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| Authors: | ZENG Zhezhao XIAO Yafen JIANG Jie ZHU Jingtao |
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| Affiliation: | 1.College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410076, China2.Yueyang City Power Bureau, Yueyang, Hunan 414000, China |
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| Abstract: | Aiming at second-order nonlinear systems, a PID neural-network control approach using the Gaussian basis functions as a neurons excitation functions is proposed. This method uses the Gaussian basis functions to simulate the curves of the PID parameters following error changes, and uses neural network algorithm online to adjust the coefficient of the simulation curves. Thereby the nonlinear control strategy is obtained. The intelligent control method on the nonlinear PID is implemented based on the Gaussian basis neural-network. The simulation results show that the approach achieves a good nonlinear control effect, so it has a broad prospect of applications in the industrial fields. |
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| Keywords: | nonlinear Proportion-Integral-Derivative（PID） Gaussian basis neural-network intelligent control |
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