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Title: Optimal Design of a Hybrid Cable Driven Parallel Robot for Desired Trajectory and Wrench Box
Authors: Chawalit Khanakornsuksan
Theeraphong Wongratanaphisan
Authors: Chawalit Khanakornsuksan
Theeraphong Wongratanaphisan
Keywords: Engineering
Issue Date: 1-Jun-2020
Abstract: © 2020, Chinese Mechanical Engineering Society. All right reserved. A hybrid cable-driven planar parallel robot (HCDPPR) is a parallel mechanism which exploits the high-force capacity of cables in combination with rigid links. In this study, method for optimal design synthesis of the HCDPPR is presented. The HCDPPR considered consists of a serial link chain, one linear actuator and two actuating cables. The linear actuator together with the two cables produce three-degree-of-freedom motion for a mobile platform (MP) in a vertical plane. These cables help to reduce system inertia and increase workspace compared to all-rigid-linkage system. The rigid links help to avoid redundant actuating requirement and potential cable tangling problem that may occur in an all-cable system. The location of cable attachments and size of connecting rod are the function of cable tension and MP motion which affect to the capability of motor. In this study, an optimal design method, based on particle swarm optimization (PSO) is proposed to minimize cable tensions for a range of given wrenches applied on the MP. The constraints are the path that the MP must follow over a range of MP's orientation and the cables are always in tension. Optimized parameters include the position of cable attachment on the base and rigid link, the length of the rigid link and mass of MP. In addition, the wrench box is included in the design algorithm to include the uncertainty wrench over operation. The optimal design method will be suitable for many proposes. Examples that demonstrate how optimized algorithm works are given. The proposed structure of the robot has potential for use an automatic gait machine as cables can provide large range of motion and high force requirement.
ISSN: 02579731
Appears in Collections:CMUL: Journal Articles

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