电子衍射谱仪探测负载惯量优化控制

Optimization Control of the Moment of Inertia on the Electronic Diffraction Spectrometer

常规的高精度控制策略很难量化地计入时变非线性、大范围变化的负载惯量,而特定场合下负载惯量大范围非线性变化对伺服系统精度的影响是不容忽视的。为此使用正则化径向基神经网络对负载惯量的变化进行预测,并在此基础上设计了大型中子衍射运动平台伺服控制系统的高精度控制策略。所设计的径向基神经网络不仅能够较好地预测负载惯量,便利地将惯量变化映射到控制策略,而且基于惯量预测控制策略的高精度控制系统是全局渐进稳定的。对考虑负载惯量变化的大型中子衍射平台的高精控制系统,在MATLAB里进行了建模仿真检验,仿真结果表明,运用所设计控制策略的高精控制系统很好地抑制了非线性负载惯量的影响,提高了运动平台在速度跟踪、位置跟踪方面的精度。

For the properties of time-varying and nonlinearity of the load,the change of the load hardly is token into account,quantitatively. A wide range of change of the load is a non-ignorable factor in the high precision servo control system. In this paper,a new predictive control strategy for the variation of the moment of inertia of the load was proposed by using radial basis function neural network,and the high precision strategy for the neutron diffraction motion platform was designed. The designed predictive control strategy achieved not only the prediction and the mapping from the change of the moment of inertia to the high precision control,but also the convergence of the proposed control system. The performance of the proposed control system was investigated through extensive simulations in MATLAB. The effect of the nonlinear moment of inertia of the load was well suppressed and the motion platform can get satisfactory results in the aspects of speed tracking and location tracking.