A self-tuning PID design based on wavelet neural network using Lyapunov method

M. Farahani, S. Ganjefar, M. Alizadeh
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引用次数: 2

Abstract

This paper presents an adaptive self-tuning PID controller based on the Lyapunov method. To tune the gains of PID controller, a self-tuning algorithm derived by the Lyapunov method is employed. Hence, the control error converges to zero and the stability of the controlled system is guaranteed. To accommodate the controller, the wavelet neural network (WNN) is used. The simulation results are used to demonstrate the effectiveness of designed controller. With the proposed controller, the controlled system possesses the advantages of good tracking control performance and robustness to unknown process.
基于Lyapunov方法的小波神经网络自整定PID设计
提出了一种基于李雅普诺夫方法的自适应自整定PID控制器。为了对PID控制器的增益进行整定,采用了由李雅普诺夫方法导出的自整定算法。因此,控制误差收敛于零,保证了被控系统的稳定性。为了适应控制器,采用了小波神经网络(WNN)。仿真结果验证了所设计控制器的有效性。该控制器具有良好的跟踪控制性能和对未知过程的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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