庞哲楠, 张国良, 吴戈, 羊帆, 陈志侃. 自由漂浮空间机器人避奇异规划—跟踪算法[J]. 信息与控制, 2016, 45(3): 348-354. DOI: 10.13976/j.cnki.xk.2016.0348
引用本文: 庞哲楠, 张国良, 吴戈, 羊帆, 陈志侃. 自由漂浮空间机器人避奇异规划—跟踪算法[J]. 信息与控制, 2016, 45(3): 348-354. DOI: 10.13976/j.cnki.xk.2016.0348
PANG Zhenan, ZHANG Guoliang, WU Ge, YANG Fan, CHEN Zhikan. Planning and Tracking Algorithm Based on Singularities Avoidance for Free-floating Space Robot[J]. INFORMATION AND CONTROL, 2016, 45(3): 348-354. DOI: 10.13976/j.cnki.xk.2016.0348
Citation: PANG Zhenan, ZHANG Guoliang, WU Ge, YANG Fan, CHEN Zhikan. Planning and Tracking Algorithm Based on Singularities Avoidance for Free-floating Space Robot[J]. INFORMATION AND CONTROL, 2016, 45(3): 348-354. DOI: 10.13976/j.cnki.xk.2016.0348

自由漂浮空间机器人避奇异规划—跟踪算法

Planning and Tracking Algorithm Based on Singularities Avoidance for Free-floating Space Robot

  • 摘要: 针对路径相关空间内自由漂浮空间机器人无法进行有效跟踪控制的问题,设计了一种避奇异轨迹规划—跟踪算法,用于完成路径相关空间机械臂末端轨迹跟踪控制的任务.首先,分析奇异条件并设定安全边界曲线,求解回避奇异的基座姿态角阈值,从而得到避奇异参考轨迹及初始状态值.接着,利用自由漂浮空间机器人非线性动力学模型具有状态依赖参数的类线性结构特点,基于状态依赖Riccati方程设计跟踪控制器对末端速度进行跟踪,保证闭环系统的局部渐近稳定性.所提方法克服了传统方法将工作空间约束在路径无关空间的缺点.仿真结果表明,该算法具有比比例微分(proportional derivative,PD)控制更高的跟踪精度.同时,在存在输入干扰的情况下仍然能够实现有效跟踪.

     

    Abstract: To address the problem of poor tracking and control in free-floating space robots working in path-dependent workspaces (PDWs), in this paper, we propose a trajectory planning and tracking algorithm based on singularities avoidance to facilitate the trajectory tracking task of the end-effector. First, we analyze the singularity condition and design a safe margin, and then determine a trajectory with singularity avoidance and the initial configurations by solving the margin value of the base altitude. Secondly, since the nonlinear dynamic model of the free-floating space robot is characterized by a linear-like structure with a state-dependent coefficient, we design the tracking controller based on the state-dependent Riccati equation (SDRE) to track the velocity of the end-effector. This guarantees the locally asymptotical stability of the closed-loop system. As a result, we can overcome the shortcoming of traditional methods of the workplace being limited to path-independent workspaces (PIWs). The simulation results show than, compared to PD control, the proposed algorithm has better tracking accuracy and achieves effective tracking when subjected to input disturbance.

     

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