Control of an Anthropomorphic Manipulator using LuGre Friction Model - Design and Experimental Validation
Khurram Ali, Adeel Mehmood, Israr Muhammad, Sohail Razzaq, Jamshed Iqbal
COMSATS University Islamabad University of Hull
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Automation technology has been extensively recognized as an emerging field in various industrial applications. Recent breakthrough in flexible automation is primarily due to deployment of robotic arms or manipulators. Autonomy in these manipulators is essentially linked with the advancements in non-linear control systems. The objective of this research is to propose a robust control algorithm for a five degree of freedom (DOF) robotic arm to achieve superior performance and reliability in the presence of friction. A friction compensation-based non-linear control has been proposed and realized for the robotic manipulator. The dynamic model of the robot has been derived by considering the dynamic friction model. The proposed three-state model is validated for all the joints of the manipulator. The integral sliding mode control (ISMC) methodology has been designed; the trajectories of system every time begin from the sliding surface and it eliminates the reaching phase with assistance of integral term in the sliding surface manifold. The designed control law has been first simulated in Matlab/Simulink environment to characterize the control performance in terms of tracking of various trajectories. The results confirm the effectiveness of the proposed control law with model-based friction compensation. The transient parameters like settling and peak time have improvement as well have better results with friction than without considering the friction. The proposed control law is then realized on an in-house developed autonomous articulated robotic rducational platform (AUTAREP) and NI myRIO hardware interfaced with LabVIEW. Experimental results also witnessed the trajectory tracking by the robotic platform.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程Dynamics and Control of Mechanical Systems
Adaptive Control of Nonlinear Systems · Robotic Mechanisms and Dynamics
参考文献 28
此处列出前 3 条
引用本文 9
按被引量排序,此处列出前 3 条