采用改进的单神经元PID控制算法提高光栅拼接精度的方法

为获得米量级以上的大口径光栅,光栅拼接技术已被公认为是一种经济可行的方法。而在光栅拼接中,光栅拼接稳定性的控制是核心问题之一,因此,在较高拼接精度的要求条件下(错位误差在纳米量级,角度误差在亚微弧度量级),寻求有效合理的比例积分微分(PID)闭环控制算法显得异常重要。将基于BP神经网络的整定方法应用到PID控制中,将传统的用零初态时过程加入单位阶跃输出的第一个值用计算符号函数值来代替,实现了单神经元自适应PID控制;在此基础上,为了改善系统响应初期的上升时间,采用变化神经元比例系数的值来代替常量K值的学习算法。通过仿真分析表明,提出的控制算法使系统响应具有好的快速性的同时又不会产生大的超调量;实验结果也表明改进的控制算法能保证其光栅拼接误差控制精度。

Advancing Precision of Grating Tiling with Modified Single Neuron Adaptive PID Control Algorithm

Grating tiling which is considered as a feasible technology can be used to obtain multiple-meter-sized large-aperture gratings, and stability control is one of key problems. So, it is important to find available and fit proportion integration differentiation (PID) closed loop control in required high accuracies condition (submicroradian orientations and nanometer positions). In this paper, by means of the principle of back propagation (BP) nerve net modified PID controller, the first value that a system in zero initial conditions using step response produces is replaced with sign function to achieve single neuron adaptive PID control, and based on that, in order to improve the risetime of the system at the beginning of the response, a changeable neuron proportionality coefficient replaces the constant K value. Simulation result indicates that the proposed control algorithm will not bring greater overshoot with quicker risetime than the traditional PID controller; and the experimental result indicates that the proposed control algorithm can guarantee the precision of the grating-tiling.