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Design and Optimization of a Control Framework for Robot Assisted Additive Manufacturing Based on the Stewart Platform

Tariku Sinshaw Tamir, Gang Xiong, Xisong Dong, Qihang Fang, Sheng Liu, Ehtisham Lodhi, Zhen Shen*, and Fei-Yue Wang
International Journal of Control, Automation, and Systems, vol. 20, no. 3, pp.968-982, 2022

Abstract : Additive manufacturing, also known as 3D printing, is an emerging technology. The existing additive manufacturing technologies deploy a 3-axis printing mechanism where the material accumulation grows only in the z-direction. This results in limited printing freedom. Apart from this, support structures are needed to print overhang structures. Removal of these supports ultimately reduces print quality. This paper proposes a novel robotassisted additive manufacturing along with a control system framework, which possesses multi-directional printing without support structures. Taking the advantage of its high stiffness and high payload-to-weight ratio, a 6-degree of freedom Stewart platform manipulator is designed to substitute the printer build plate. The kinematics and dynamics of the manipulator is formulated. Then, an extended proportion-derivation sliding mode controller is designed for trajectory tracking. The modified grey wolf optimization algorithm is applied to compute the optimal controller parameters. The integral absolute error (IAE) is used as a cost function and its minimum value is reached in the iteration interval [75,100]. The analytical model simulation in MATLAB is run for 10 seconds, and the results show that the desired length trajectories of the six legs of the manipulator are achieved after 3.5 seconds. The performance of the analytical model is verified on the automated dynamic analysis of mechanical systems (ADAMS).

Keyword : Additive manufacturing, extended proportion-derivation sliding mode controller, grey wolf optimization, print quality, Stewart platform.

 
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