吊装用起重机自动定位视觉伺服控制

Vision servo control for automatic positioning of hoisting crane

传统起重机自动定位方法精度低,稳定性差,不能形成真正的闭环控制,现有起重机视觉定位方法普遍存在抗扰动性能差和视觉雅可比矩阵参数难以获得等问题。为了解决外部扰动影响视觉伺服定位精度和稳定性的问题,建立了扰动工况下吊装末端执行器的位姿数学模型,提出一种基于自抗扰控制器的视觉伺服扰动抑制方法。根据图像投影特性,得出雅可比矩阵参数与图像特征微分关系方程,设计了雅可比矩阵参数估计值自适应更新率,并建立闭环动力学方程。根据图像特征误差,构建李亚普诺夫函数,给出了系统稳定性证明。进行仿真与实验分析,结果表明:当视觉误差收敛后,位置与速度曲线均趋于零值,说明在视觉不确定性和恒定、瞬时扰动的情况下,本文方法仍然具有令人满意的定位精度。通过与其他控制方法的对比结果分析可知,本文方法在保证视觉伺服系统定位精度的同时,能够加快视觉误差的收敛速度,具有更好的稳定性,因此,适用于吊装用起重机自动定位视觉伺服系统。

The traditional crane automatic positioning method has low accuracy and poor stability,which can not form a real closed-loop control.The existing crane vision positioning methods generally have problems such as poor anti-interference performance,difficulty in convergence of vision error and difficulty in obtaining visual Jacobian matrix parameters.To solve the problem that the external disturbance affects the positioning accuracy and stability of visual servo system,this paper establishes the mathematical model of the position and attitude of the end effector under the disturbance condition,and proposes a visual servo disturbance suppressing method based on the Active Disturbance Rejection Controller.According to the characteristics of image projection,the relation between the parameters of Jacobian matrix and the differential of image feature is obtained,the adaptive updating rate of the parameters of Jacobian matrix is designed,and the closed-loop dynamic equation is established.According to the image feature error,the Lyapunov function is constructed and the system stability is proved.The simulation result shows that when the visual error converges,the position and velocity curves tend to zero.The method in this paper has satisfactory positioning accuracy in the case of visual uncertainty and external disturbance.It can ensure the positioning accuracy of the visual servo system and accelerate the convergence speed of the visual error under the disturbance condition.So,it is suitable for the control of the automatic positioning visual servo system of the hoisting crane.