基于神经网络的压电SSA信号解耦的仿真研究
Research on simulation of piezoelectric SSA signal decoupling based on neural network
本文就压电自感知执行的关键问题——信号解耦进行了研究,在Dosch等提出的桥式电路的基础上,结合神经网络预测控制技术与所构建了虚拟被控对象,提出了基于神经网络预测控制的压电SSA混合信号自适应解耦方法。在Matlab/simulik环境下对该自适应解耦方法进行了大量的仿真研究。仿真结果表明:利用该信号解耦方法解耦的相对误差约为0.25%,有着很好的解耦效果。
his paper researches on the signal decoupling, the key issue of self-sensing actuator of piezoelectricity, puts forward the adaptive decoupling method of piezoelectricity SSA mixed signal basing on ANNPC, on the basis of bridge circuit put forward by Dosch, etc, combining the technology of ANNPC and the virtual controlled device it built. This paper also carries on much simulation research on this adaptive decoupling method under the Matlab or simulik circumstances. The simulation results indicate that the relative error of decoupling using this signal decoupling method is about 0.25 percent, having a good effect on decoupling.
卢倩、程光明、孟凡玉、朱志伟、曾平
电子电路电子技术应用自动化技术、自动化技术设备
压电自感知执行神经网络预测控制自适应解耦
PiezoelectricitySelf-sensing actuateNeural network predictive controlAdaptive decoupling
卢倩,程光明,孟凡玉,朱志伟,曾平.基于神经网络的压电SSA信号解耦的仿真研究[EB/OL].(2009-04-10)[2025-08-19].http://www.paper.edu.cn/releasepaper/content/200904-337.点此复制
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