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Inverse pseudo-random binary sequence design and its application in identifying of the SCARA-type manipulator

机译:逆伪随机二进制序列设计及其在识别Scela型机械手时的应用

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The design of Inverse pseudo-random binary sequence (IPRBS) for the plant identification is presented. There exist two problems, the burden of identification experimental working amount based on the frequency response method and the identification precision sensitivity to the input-excitation signal based on Recursive Least Square with forgetting factor (RFF). We solve the problems using a novel identification method, which combines RFF algorithm through frequency response analysis. The nominal model parameters are identified on the basis of frequency response analysis, in which the frequency bandwidth of harmonic input is limited, and frequency resolution is coarse. Based on this, the shift-impulse cycle of IPRBS as identification input can be calculated with the iteration-optimum method, and the model parameters can also be identified optimally in the procedure. The method is applied to the design of motion control system based on disturbance observer (DOB) of SCARA-type manipulator using Windows NT and VenturCom''s real-time extension module (RTX) environment.
机译:介绍了工厂识别的逆伪随机二进制序列(IPRB)的设计。存在两个问题,基于频率响应方法的识别实验工作量的负担以及基于忘记因子(RFF)的递归最小二乘的输入激励信号的识别精度敏感性。我们使用一种新颖的识别方法解决问题,该方法通过频率响应分析结合了RFF算法。基于频率响应分析来识别标称模型参数,其中谐波输入的频率带宽是有限的,并且频率分辨率是粗糙的。基于此,可以利用迭代 - 最佳方法计算IPRBS作为识别输入的移位 - 脉冲周期,并且还可以在过程中最佳地识别模型参数。使用Windows NT和Venturcom'实时扩展模块(RTX)环境基于Scara型机械手的干扰观察器(DOB)的运动控制系统设计。

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