用模糊自适应滑模控制提升圆柱机械臂轨迹跟踪精度
Robust adaptive fuzzy sliding mode control for trajectory tracking for of cylindrical manipulator
- 融合模糊逻辑与滑模控制，自适应补偿系统不确定性
- 仿真显示轨迹跟踪误差降低，抗干扰能力显著增强
- 适合高精度工业机器人控制，如CNC和3D打印场景
本研究提出一种鲁棒自适应模糊滑模控制（AFSMC）方法，以提升圆柱形机械臂在数控加工和3D打印等场景中的轨迹跟踪性能。该方法结合模糊逻辑与滑模控制（SMC），利用模糊逻辑逼近系统不确定动态，同时保持滑模控制的强鲁棒性。在MATLAB/Simulink中的仿真结果表明，相比传统方法，AFSMC显著提高了轨迹跟踪精度、系统稳定性和扰动抑制能力。研究验证了AFSMC在工业机器人控制中的有效性，有助于提升制造过程的精度。
原文摘要 · Abstract (English)
This research proposes a robust adaptive fuzzy sliding mode control (AFSMC) approach to enhance the trajectory tracking performance of cylindrical robotic manipulators, extensively utilized in applications such as CNC and 3D printing. The proposed approach integrates fuzzy logic with sliding mode control (SMC) to bolster adaptability and robustness, with fuzzy logic approximating the uncertain dynamics of the system, while SMC ensures strong performance. Simulation results in MATLAB/Simulink demonstrate that AFSMC significantly improves trajectory tracking accuracy, stability, and disturbance rejection compared to traditional methods. This research underscores the effectiveness of AFSMC in controlling robotic manipulators, contributing to enhanced precision in industrial robotic applications.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。