STEWART PLATFORM DYNAMICS MODEL IDENTIFICATION

V. Zozulya, S. Osadchy, S. N. Nedilko
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Abstract

Context. At the present stage, with the current demands for the accuracy of motion control processes for a moving object on a specified or programmable trajectory, it is necessary to synthesize the optimal structure and parameters of the stabilization system (controller) of the object, taking into account both real controlled and uncontrolled stochastic disturbing factors. Also, in the process of synthesizing the optimal controller structure, it is necessary to assess and consider multidimensional dynamic models, including those of the object itself, its basic components, controlled and uncontrolled disturbing factors that affect the object in its actual motion. Objective. The aim of the research, the results of which are presented in this article, is to obtain and assess the accuracy of the Stewart platform dynamic model using a justified algorithm for the multidimensional moving object dynamics identification. Method. The article employs a frequency-domain identification method for multidimensional stochastic stabilization systems of moving objects with arbitrary dynamics. The proposed algorithm for multidimensional moving object dynamics model identification is constructed using operations of polynomial and fractional-rational matrices addition, multiplication, Wiener factorization, Wiener separation, and determination of dispersion integrals. Results. As a result of the conducted research, the problem of identifying the dynamic model of a multidimensional moving object is formalized, illustrated by the example of a test stand based on the Stewart platform. The outcomes encompass the identification of the dynamic model of the Stewart platform, its transfer function, and the transfer function of the shaping filter. The verification of the identification results confirms the sufficient accuracy of the obtained models. Conclusions. The justified identification algorithm allows determining the order and parameters of the linearized system of ordinary differential equations for a multidimensional object and the matrix of spectral densities of disturbances acting on it under operating conditions approximating the real functioning mode of the object prototype. The analysis of the identification results of the dynamic models of the Stewart platform indicates that the primary influence on the displacement of the center of mass of the moving platform is the variation in control inputs. However, neglecting the impact of disturbances reduces the accuracy of platform positioning. Therefore, for the synthesis of the control system, methods should be applied that enable determining the structure and parameters of a multidimensional controller, considering such influences.
斯图尔特平台动力学模型识别
背景。现阶段,随着对运动物体在指定或可编程轨迹上的运动控制过程精度的要求不断提高,有必要综合考虑实际受控和非受控随机干扰因素,确定物体稳定系统(控制器)的最佳结构和参数。此外,在合成最佳控制器结构的过程中,有必要评估和考虑多维动态模型,包括物体本身、其基本组件、影响物体实际运动的受控和非受控干扰因素的动态模型。研究目的本文介绍的研究结果旨在利用一种合理的多维运动物体动态识别算法,获得并评估斯图尔特平台动态模型的准确性。研究方法文章针对具有任意动力学特性的运动物体多维随机稳定系统采用了频域识别方法。所提出的多维运动物体动力学模型识别算法采用了多项式和分式有理矩阵加法、乘法、维纳因式分解、维纳分离和离散积分确定等运算。研究结果作为研究成果,以基于斯图尔特平台的试验台为例,对确定多维运动物体动态模型的问题进行了形式化。研究成果包括识别斯图尔特平台的动态模型、其传递函数和整形滤波器的传递函数。对识别结果的验证证实了所获模型的足够准确性。结论。通过合理的识别算法,可以确定多维物体线性化常微分方程系统的阶次和参数,以及在近似于物体原型实际运行模式的工作条件下,作用于该物体的干扰频谱密度矩阵。对斯图尔特平台动态模型的识别结果分析表明,对移动平台质心位移的主要影响因素是控制输入的变化。然而,忽略干扰的影响会降低平台定位的精度。因此,在合成控制系统时,应采用能够确定多维控制器结构和参数的方法,同时考虑到这些影响因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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