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Algorithms 2018, 11(1), 7; doi:10.3390/a11010007

Optimization Design by Genetic Algorithm Controller for Trajectory Control of a 3-RRR Parallel Robot

School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, China
Author to whom correspondence should be addressed.
Received: 21 November 2017 / Revised: 30 December 2017 / Accepted: 12 January 2018 / Published: 15 January 2018
(This article belongs to the Special Issue Algorithms for PID Controller)
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In order to improve the control precision and robustness of the existing proportion integration differentiation (PID) controller of a 3-Revolute–Revolute–Revolute (3-RRR) parallel robot, a variable PID parameter controller optimized by a genetic algorithm controller is proposed in this paper. Firstly, the inverse kinematics model of the 3-RRR parallel robot was established according to the vector method, and the motor conversion matrix was deduced. Then, the error square integral was chosen as the fitness function, and the genetic algorithm controller was designed. Finally, the control precision of the new controller was verified through the simulation model of the 3-RRR planar parallel robot—built in SimMechanics—and the robustness of the new controller was verified by adding interference. The results show that compared with the traditional PID controller, the new controller designed in this paper has better control precision and robustness, which provides the basis for practical application. View Full-Text
Keywords: kinematics model; virtual bench; genetic algorithm controller; robustness kinematics model; virtual bench; genetic algorithm controller; robustness

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sheng, L.; Li, W. Optimization Design by Genetic Algorithm Controller for Trajectory Control of a 3-RRR Parallel Robot. Algorithms 2018, 11, 7.

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