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INVERSE PSEUDO-RANDOM BINARY SEQUENCE DESIGN FOR SCARA-TYPE MANIPULATOR

机译:斯卡拉型机械手的伪伪随机二值序列设计

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摘要

The design of inverse pseudo-random binary sequence (IPRBS) for the plant identification is presented. There exist two problems, i.e., 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 (RLS) 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 a SCARA-type manipulator using Windows NT and VenturCorn's real-time extension module (RTX) environment.
机译:提出了用于植物识别的逆伪随机二进制序列(IPRBS)的设计。存在两个问题,即基于频率响应方法的识别实验工作量的负担和基于具有遗忘因子(RFF)的递归最小二乘(RLS)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了这些问题,该方法结合了RFF算法和频率响应分析。在频率响应分析的基础上,确定标称模型参数,在该模型中,谐波输入的频率带宽受到限制,频率分辨率较粗。基于此,可以通过迭代计算出IPRBS作为识别输入的偏移脉冲周期,最佳方法,并且模型参数也可以在过程中进行最佳识别。该方法应用于基于Windows NT和VenturCorn实时扩展模块(RTX)环境的SCARA型机械手的扰动观察器(DOB)的运动控制系统的设计。

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