Ma Zhe, Su Jianbo
Department of Automation; Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, PR China.
Department of Automation; Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, PR China.
ISA Trans. 2015 Nov;59:193-204. doi: 10.1016/j.isatra.2015.07.003. Epub 2015 Aug 29.
In this paper, an uncalibrated visual servoing scheme with optimal disturbance rejection performance is proposed based on disturbance observer (DOB). Comparing with traditional uncalibrated methods, which estimate online the hand-eye relationship characterized by varying image Jacobian, the uncertainty of image Jacobian is eliminated via DOB to approach a given nominal model in this paper. By solving a constrained optimization problem transformed into an H∞ control framework, the disturbance rejection performance is optimized while ensuring the robust stability of the closed-loop visual servoing system. The controller is based on the nominal image Jacobian matrix, thus avoiding singularities and local minima. Simulations and experiments show that the proposed scheme performs better in tracking an object than traditional algorithms. The disturbance and image noise rejection performance is verified.
本文提出了一种基于干扰观测器（DOB）的具有最优干扰抑制性能的无标定视觉伺服方案。与传统的无标定方法相比，传统方法在线估计以变化的图像雅可比矩阵为特征的手眼关系，而本文通过DOB消除图像雅可比矩阵的不确定性，以逼近给定的标称模型。通过求解转化为H∞控制框架的约束优化问题，在确保闭环视觉伺服系统鲁棒稳定性的同时，优化了干扰抑制性能。该控制器基于标称图像雅可比矩阵，从而避免了奇异性和局部最小值。仿真和实验表明，所提方案在跟踪物体方面比传统算法表现更好。干扰和图像噪声抑制性能得到了验证。
