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عدد المساهمات : 18994 التقييم : 35488 تاريخ التسجيل : 01/07/2009 الدولة : مصر العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى
| موضوع: بحث بعنوان Practical Velocity Tracking Control of a Parallel Robot Based on Fuzzy Adaptive Algorithm الخميس 28 يوليو 2022, 11:24 pm | |
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أخواني في الله أحضرت لكم بحث بعنوان Practical Velocity Tracking Control of a Parallel Robot Based on Fuzzy Adaptive Algorithm Research Article Zude Zhou,1,2 Wei Meng,1,2 Qingsong Ai,1,2 Quan Liu,1,2 and Xiang Wu2 1 School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China 2 Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Wuhan University of Technology, Ministry of Education, Wuhan, Hubei 430070, China Correspondence should be addressed to Qingsong Ai; qingsongai@whut.edu.cn Received 14 March 2013; Revised 20 June 2013; Accepted 20 June 2013 Academic Editor: Shane Xie
و المحتوى كما يلي :
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Due to the advantages of its compact structure and high operation accuracy, the six degrees of freedom (6-DOF) parallel platform has been widely used as a carrier of medical rehabilitation devices. Fuzzy adaptive algorithm does not depend on the mathematical model of controlled object, which possesses good nonlinear characteristics. Those entire features make it an effective method to control such complex and coupling platforms. To facilitate the application of robotics in lower limb rehabilitation fields, a robotic system in practical environment was established based on kinematics modeling of the 6-DOF Stewart-based platform. In order to improve the velocity tracking accuracy, this paper proposed a closed-loop control strategy based on fuzzy adaptive algorithm. The velocity feedback information was utilized to modify the PID parameters adaptively in realtime through fuzzy inference units. Several experiments in practical environment were conducted, and the results demonstrated that the proposed algorithm could effectively reduce the speed jitter, enhance the position and velocity tracking precision of the robot, and the reliability and robustness of the system could also be ensured Conclusion and Future Work During the motion control of the rehabilitation robot, the system may become unstable due to the uncertain variations of the system loads and dynamic parameters, which would lead to the secondary injury of the patients. Therefore, it is of great significance to maintain the trajectory and velocity tracking accuracy and stability for medical purpose [18]. This paper aims at designing an effective method to control the Stewart robot used for lower limb rehabilitation. Based on the study on parallel robot’s kinematic model, a prototype of 6- DOF parallel robot control system is established, and accordingly a fuzzy PID adaptive controller is proposed for velocity close-loop control. The experimental results performed in the actual experiment demonstrate that applying the proposed adaptive fuzzy control method to 6-DOF parallel robot manipulator is reasonable and valid; the position and velocity tracking accuracy can be greatly improved. Currently, it seems that there are not enough realistic applications of the parallel robot; thus it is worthwhile to propose a fuzzy adaptive controller that can achieve a good performance in the actual environment and put it into practice for medical purpose. The future works involve improving the dynamic response of such parallel platform and obtaining a better trajectory tracking performance by combining the fuzzy controller with other advanced control techniques, such as neural network and sliding mode control strategies. Furthermore, in order to improve the rehabilitation results, force feedback between the robot and the patient should be taken into consideration; putting the position/force hybrid control and impedance control into practice is also important in this field. Finally, in order to implement the rehabilitation control strategies in the actual environment, more attentions should be attracted to biomedical signals processing, human-machine interface, and the rehabilitation assessment strategies.
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