张美凤, 蔡建文. DVD光学头的RBF神经网络自适应PID控制器设计[J]. 应用光学, 2015, 36(6): 852-856. DOI: 10.5768/JAO201536.0601006
引用本文: 张美凤, 蔡建文. DVD光学头的RBF神经网络自适应PID控制器设计[J]. 应用光学, 2015, 36(6): 852-856. DOI: 10.5768/JAO201536.0601006
Zhang Mei-feng, Cai Jian-wen. Design of RBF neural network adaptive PID controller of DVD pick-up head[J]. Journal of Applied Optics, 2015, 36(6): 852-856. DOI: 10.5768/JAO201536.0601006
Citation: Zhang Mei-feng, Cai Jian-wen. Design of RBF neural network adaptive PID controller of DVD pick-up head[J]. Journal of Applied Optics, 2015, 36(6): 852-856. DOI: 10.5768/JAO201536.0601006

DVD光学头的RBF神经网络自适应PID控制器设计

Design of RBF neural network adaptive PID controller of DVD pick-up head

  • 摘要: 为了使三维光存储技术的应用水平得到提高,以DVD伺服技术、双光子吸收技术为基础组建了一套信息存储系统。针对DVD光学读取头系统,采用RBF神经网络自适应PID控制器进行控制,充分利用RBF神经网络的自学习和全局非线性逼近能力,在线调整修正PID控制器的3个参数,使其达到一种最优控制,并通过MATLAB软件进行了计算机仿真。由仿真结果可以得出:通过应用RBF神经网络自适应PID控制算法,系统单位阶跃响应的调整时间为0.25 s,并使系统的超调量降低到几乎为零。

     

    Abstract: In order to improve the practical level of two-photon 3D optical storage technology,the information storage system was built based on DVD servo technology and two-photon absorption technology. The radial basis function (RBF) neural network self-adjusting proportional-integral-derivative (PID) control algorithm was used to built the simulation model of PID control system based on the transfer function of DVD pick-up head.The parameters of PID controller were adjusted online by the ability of the RBF neural network self learning and global nonlinear strong approximation and simulated by Matlab. It is proved that the settling time of the step response of the system is shortened to 0.25s and the overshoot of the system reduces to almost zero after applying the RBF neural network adaptive PID control algorithm.

     

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