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国防科学技术大学 机电工程与自动化学院,湖南 长沙,410073
收稿日期:2014-07-27,
修回日期:2014-08-20,
纸质出版日期:2015-02-25
移动端阅览
廖洪波, 范世珣, 黑墨等. 光电稳定平台伺服系统动力学建模与参数辨识[J]. 光学精密工程, 2015,23(2): 477-484
LIAO Hong-bo, FAN Shi-xun, Hei Mo etc. Modeling and parameter identification for electro-optical stabilized platform servo systems[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 477-484
廖洪波, 范世珣, 黑墨等. 光电稳定平台伺服系统动力学建模与参数辨识[J]. 光学精密工程, 2015,23(2): 477-484 DOI: 10.3788/OPE.20152302.0477.
LIAO Hong-bo, FAN Shi-xun, Hei Mo etc. Modeling and parameter identification for electro-optical stabilized platform servo systems[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 477-484 DOI: 10.3788/OPE.20152302.0477.
针对光电稳定平台伺服系统模型参数辨识问题
提出了线性和非线性模型参数分离辨识方法。在线性模型参数辨识过程中
利用差动逆
M
序列信号作为输入
相应的响应信号作为输出
并应用最小二乘方法辨识线性离散模型参数
从而降低非线性因素的影响。在非线性模型参数辨识过程中
以LuGre摩擦模型为基础
针对摩擦和不平衡质量相互耦合的问题
提出了考虑不平衡质量的LuGre模型静态参数辨识方法;然后
利用电流信号作为摩擦力测量值
对LuGre模型动态参数进行辨识
得到包含不平衡质量和动态摩擦的系统非线性部分模型参数。构建了单轴光电稳定平台实验系统
利用本文提出的方法对实验系统动力学模型参数进行了辨识。结果表明:质量不平衡力矩的辨识值为0.183 N·m
略高于理论值0.18 N·m
满足辨识精度要求。实验证实提出的辨识方法可以实现对模型线性与非线性参数的有效辨识。
A separated model parameter identification method for electro-optical stabilized platform servo systems was presented. The model of servo systems was separated into a linear part and a nonlinear part. In the process of parameter identification of the linear model
a differential inverse
M
sequence signal was utilized to excited servo systems
and least square method was used to identify the parameters of the linear discrete model part to reduce the influence of the nonlinear dynamics. In the process of parameter identification of the nonlinear model
the coupling dynamics between friction and unbalanced mass was considered
and the static parameters of the LuGre model and the parameters of the unbalanced mass model were firstly identified by using the least square method; Then
the dynamic parameters of the LuGre model were obtained by friction measurement through a current signal. An experimental system for single-axis electro-optical stabilized platform was constructed
and the dynamic model parameters were indentifies by proposed method. Experimental results indicate that the identification value of unbalanced mass torque is 0.183 N·m
which is a little larger than the theoretic value 0.18 N·m
and satisfied with the identification precision. So the parameters of linear and nonlinear models can be obtained by the presented identification method.
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