Zhang Ronghua, Wang Yaonan, Xie Wenfang, Li Pengcheng, Tan Haoran, Jiang Yiming
College of Electrical and Information Engineering, Hunan University, Changsha, 410082, Hunan, China; National Engineering Laboratory of Robot Visual Perception and Control Technology, Hunan University, Changsha, 410082, Hunan, China.
Department of Mechanical, Industrial and Aerospace, Concordia University, Montreal, H3G2W1, Quebec, Canada.
ISA Trans. 2025 Sep;164:197-210. doi: 10.1016/j.isatra.2025.05.022. Epub 2025 May 22.
The use of multiple robots to manufacture composite components represents a critical development direction for fiber placement systems (FPSs). In multi-robotic fiber placement systems (MRFPSs) with heterogeneous mechanical structures, robots collaborate to perform fiber placement tasks. Consequently, robot synchronization emerges as a primary factor in determining the performance of the fiber placement process. However, the difficulty in establishing accurate system models and the presence of disturbances are two significant challenges to achieving precise robot synchronization. Additionally, the system is expected to exhibit desirable dynamic characteristics, such as finite-time error convergence. To address these issues and requirements, we propose a novel adaptive finite-time synchronization control (AFSC) algorithm for the system. Specifically, a finite-time sliding mode observer is developed to handle kinematic uncertainty. A novel fast non-singular terminal sliding mode (FNTSM) manifold is constructed in the AFSC algorithm. Moreover, the control algorithm integrates an adaptive law to handle dynamic uncertainty and an adaptive term to counteract disturbances. Performance analysis demonstrates that the AFSC ensures that the coupled, synchronization, and tracking errors converge to zero within finite time. Furthermore, simulations and experiments are conducted to validate the effectiveness of the AFSC algorithm.
使用多个机器人制造复合材料部件是纤维铺放系统（FPS）的一个关键发展方向。在具有异构机械结构的多机器人纤维铺放系统（MRFPS）中，机器人协作执行纤维铺放任务。因此，机器人同步成为决定纤维铺放过程性能的一个主要因素。然而，建立精确的系统模型存在困难以及干扰的存在是实现精确机器人同步的两个重大挑战。此外，该系统还应表现出理想的动态特性，如有限时间误差收敛。为了解决这些问题和满足这些要求，我们为该系统提出了一种新颖的自适应有限时间同步控制（AFSC）算法。具体而言，开发了一种有限时间滑模观测器来处理运动学不确定性。在AFSC算法中构建了一种新颖的快速非奇异终端滑模（FNTSM）流形。此外，该控制算法集成了一个自适应律来处理动态不确定性和一个自适应项来抵消干扰。性能分析表明，AFSC确保耦合误差、同步误差和跟踪误差在有限时间内收敛到零。此外，还进行了仿真和实验以验证AFSC算法的有效性。
