Researches on Temperature Control Strategy of SMHS-Type 3D Printing Based on Variable Universe Fuzzy Control

Tao Wu; Yiru Tang; Dongdong Fei; Yongbo Li; Wangyong He

doi:10.20965/jaciii.2017.p0166

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JACIII Vol.21 No.1 pp. 166-171

doi: 10.20965/jaciii.2017.p0166

(2017)

Paper:

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Researches on Temperature Control Strategy of SMHS-Type 3D Printing Based on Variable Universe Fuzzy Control

Tao Wu, Yiru Tang, Dongdong Fei, Yongbo Li, and Wangyong He

School of Automation, China University of Geosciences
Wuhan 430074, China

Received:

July 8, 2016

Accepted:

October 26, 2016

Published:

January 20, 2017

Keywords:

temperature control on 3D printing, fuzzy control, variable universe, constant energy printing

Abstract

Selective micro heat sintering (SMHS)-type 3D printing technology is a widely applied method in rapid prototyping, which uses an electric heating component to sinter non-metallic powder. It requires precise control of the heating component’s energy and its sintering time. Temperature is one of the key factors that affect the forming quality of fused-type 3D printing technology. Aiming at the nonlinear and time-delay characteristics of temperature control in fused-type 3D printing, a fuzzy control method based on variable universe fuzzy control was studied. This fuzzy control method adopts a set of nonlinear expansion-contraction factors to make the variable universes change with the adaptive error, which can help acquire adaptive temperature adjustment in the rapid prototyping process control. The results of the simulation and experiment showed that the controlled temperature response was faster, the overshoot was smaller, and the stability was better compared to the conventional fuzzy proportion integration differentiation (PID) algorithm after the temperature reached the target temperature. The printed results indicated that the universe fuzzy PID control can effectively improve the accuracy of the workpiece shapes and that the density distribution of the workpiece is increased, which can help improve the forming quality.

Cite this article as:

T. Wu, Y. Tang, D. Fei, Y. Li, and W. He, “Researches on Temperature Control Strategy of SMHS-Type 3D Printing Based on Variable Universe Fuzzy Control,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.1, pp. 166-171, 2017.

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References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] H. Li, J. Yu, and C. Hilton, “Adaptive Sliding-Mode Control for Nonlinear Active Suspension Vehicle Systems Using T–S Fuzzy Approach,” IEEE Trans. Ind. Electron., Vol.60, No.8, pp. 3328-3338, 2013.

[2] [2] F. Piltan, N. Sulaiman, I. A. Talooki, and P. Ferdosali, “Control of IC Engine: Design a Novel MIMO Fuzzy Backstepping Adaptive Based Fuzzy Estimator Variable Structure Control,” Int. J. Robot. Autom., Vol.2, No.2, pp. 360-380, 2011.

[3] [3] A. L. Elshafei, K. A. El-Metwally, and A. A. Shaltout, “A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems,” Control Eng. Pract., Vol.13, No.4, pp. 413-423, 2005.

[4] [4] B. Wang, P. Shi, H. R. Karimi, J. Wang, and Y. Song, “Fuzzy Variable Structure Control for Uncertain Systems with Disturbance,” Math. Probl. Eng., Vol.29, No.4, pp. 907-921, 2012.

[5] [5] H. Li, Z. Miao, and J. Wang, “Variable universe stable adaptive fuzzy control of nonlinear system,” Sci. China, Vol.45, No.3, pp. 225-240, 2002.

[6] [6] X. Yu, H. Y. Yu, and G. G. Zhao, “Application of Variable Universe Fuzzy Control PID in Temperature Command of the Animal Building,” Int. J. Control Autom., Vol.7, No.9, pp. 1-10, 2014.

[7] [7] J. Wang, G. D. Qiao, and B. Deng, “Observer-based robust adaptive variable universe fuzzy control for chaotic system,” Chaos Soliton. Fract., Vol.23, No.3, pp. 1013-1032, 2005.

[8] [8] S. Tong and G. Liu, “Real-time simplified variable universe fuzzy control of PEM fuel cell flow systems,” Control Conf., IEEE, 2007.

[9] [9] L. Zhang, A. Cao, and Y. Du, “Variable universe fuzzy control for excitation system of HTS machine,” J. Intell. Fuzzy Syst., Vol.29, No.6, pp. 2457-2456, 2015.

[10] [10] A. Boulkroune, M. Msaad, and M. Farza, “State and output feedback fuzzy variable structure controllers for multivariable nonlinear systems subject to input nonlinearities,” Int. J. Adv. Manuf. Tech., Vol.71, No.1-4, pp. 539-556, 2014.