具有量化反馈的视觉伺服WMR控制研究
Research on WMR Control of Visual Servo with Quantitative Feedback
摘要: 针对具有外部扰动和量化反馈的图像视觉伺服移动机器人轨迹跟踪问题，提出了一种基于超螺旋算法的量化反馈控制方法，首先使用超螺旋滑模控制方案，将扰动项放入滑模高阶导数中，减少滑模控制中的抖振现象；接着将量化误差的界限放入滑模开关函数中，来抑制量化对系统稳定性的影响；通过李雅普诺夫函数证明了系统可以在有限时间收敛至与量化参数相关的较小区域内，最后通过动态调节量化参数，使系统最终可以收敛至零。通过仿真结果验证了控制方案的有效性。
Abstract: A quantitative feedback control method based on super-twisting algorithm is proposed aiming at the trajectory tracking of image visual servo mobile robot with external disturbance and quantitative feedback. Firstly, based on super-twisting sliding mode control plan, the disturbance term is put into the high-order derivative of sliding mode to reduce the chattering in sliding mode control; Secondly, the limit of quantization errors are put into sliding mode switching function to suppress the influence of quantization on system stability; it is proved by Lyapunov function that the system can converge to a small region related to quantization parameters in finite time. Finally, by dynamically adjusting quantization parameters, the system can finally converge to zero. The effectiveness of the control plan is verified by simulation results.
文章引用：杨靖伟, 孙杰. 具有量化反馈的视觉伺服WMR控制研究[J]. 人工智能与机器人研究, 2022, 11(1): 9-18. https://doi.org/10.12677/AIRR.2022.111002

参考文献

[1] 李宝全, 徐壮, 冀东. 基于单应矩阵分解的轮式移动机器人视觉伺服轨迹跟踪[J]. 天津工业大学学报, 2020, 39(3): 61-68.
[2] Cheah, C.C., Hou, S.P., Yu, Z., et al. (2010) Adaptive Vision and Force Tracking Control for Robots with Constraint Uncertainty. IEEE/ASME Transactions on Mechatronics, 15, 389-399. [Google Scholar] [CrossRef] 
[3] Liu, Y.H., Wang, H., Wang, C., et al. (2006) Uncalibrated Visual Servoing of Robots Using a Depth-Independent Interaction Matrix. IEEE Transactions on Robotics, 22, 804-817. [Google Scholar] [CrossRef] 
[4] Li, S., Ghasemi, A., Xie, W., et al. (2018) An Enhanced IBVS Controller of a 6DOF Manipulator Using Hybrid PD-SMC Method. International Journal of Control Automation and Systems, 16, 844-855. [Google Scholar] [CrossRef] 
[5] 张德伟, 刘海涛, 王仙业, 肖聚亮. 一种足式移动机器人的混合视觉伺服控制方法[J/OL]. 机械科学与技术: 1-10.[CrossRef] 
[6] 陈勇, 刘哲, 乔健, 卢清华, 谢永芳. 轮式机器人移动过程中滑模控制策略的研究[J]. 控制工程, 2021, 28(5): 963-970.
[7] 方文华. 采用改进粒子群算法优化的两关节移动机器人滑模控制研究[J]. 中国工程机械学报, 2019, 17(6): 506-509+514.
[8] 陈杰, 刘宜成, 王宏, 涂海燕. 图像视觉伺服的无人机固定时间滑模控制[J]. 电光与控制, 2021, 28(3): 24-30.
[9] 李军, 廖宇新, 李珺. 三维自适应有限时间超螺旋滑模制导律[J]. 系统工程与电子技术, 2021, 43(3): 779-788.
[10] 薛艳梅, 郝立颖. 量化参数不匹配的线性系统监督滑模控制设计[J]. 计算机工程与应用, 2015, 51(15): 22-27.
[11] 张乐乐, 苏前敏. 具有不匹配量化的非线性系统自适应滑模控制[J]. 电子科技, 2020, 33(12): 38-43.
[12] Sun, H., Hou, L., Zong, G., et al. (2018) Fixed-Time Attitude Tracking Control for Spacecraft with Input Quantization. IEEE Transactions on Aerospace and Electronic Systems, 55, 124-134. [Google Scholar] [CrossRef] 
[13] Crochiere, R.E.A (2014) Mid-Rise/Mid-Tread Quantizer Switch for Improved Idle-Channel Performance in Adaptive Coders. Bell System Technical Journal, 57, 2953-2955. [Google Scholar] [CrossRef] 
[14] 冯昱澍, 刘昆, 冯健. 航天器姿态跟踪有限时间自适应积分滑模控制[J]. 电子科技大学学报, 2021, 50(4): 527-534.

为你推荐