Volume 15, Issue 2 (4-2015)
Modares Mechanical Engineering 2015, 15(2): 147-158 |
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Moezi S A, Rafeeyan M, Ebrahimi S. Sliding mode Control of 3-RPR parallel robot on the optimal path using Cuckoo Optimization Algorithm. Modares Mechanical Engineering 2015; 15 (2) :147-158
URL: http://mme.modares.ac.ir/article-15-9922-en.html
URL: http://mme.modares.ac.ir/article-15-9922-en.html
Sliding mode Control of 3-RPR parallel robot on the optimal path using Cuckoo Optimization Algorithm
1- student/Yazd university
2-
2-
Abstract: (8236 Views)
The present study aims to implement an approach for trajectory control of a 3-RPR parallel manipulator over a path with obstacles in the workspace. For this purpose, using the spline curves approach and based on the cuckoo optimization algorithm, a smooth reference trajectory with minimum length is generated in the workspace to avoid robot collision with obstacles. The performance and accuracy of the cuckoo optimization algorithm in converging to the optimal solution is then compared with the Genetic algorithm. In the next step, the robust sliding mode control technique is adopted for trajectory control of the robot in the presence of some uncertainties. These uncertainties usually include the links length and links mass of the robot. The obtained results confirm the demanded level of performance and accuracy of the cuckoo optimization algorithm. It is also observed that the optimal trajectory with minimum length is generated using the spline curves approach. In addition, it is concluded that based on the sliding mode control technique, the robot can follow the desired trajectory very precisely in spite of the presence of the uncertainties in length and mass of the robot's links.
Keywords: Three degrees of freedom robot, path generating, Cuckoo Optimization Algorithm, genetic Optimization Algorithm, Sliding mode control, Spline Curve
Article Type: Research Article |
Subject:
robatic
Received: 2014/10/2 | Accepted: 2014/12/11 | Published: 2014/12/27
Received: 2014/10/2 | Accepted: 2014/12/11 | Published: 2014/12/27
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