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Intelligent optimal control considering dynamic posture compensation for a cantilever roadheader

Published online by Cambridge University Press:  23 June 2021

Lixia Fang Open the ORCID record for Lixia Fang [Opens in a new window] ,
Zhigang Liu  and
Miao Wu
Lixia Fang*
Affiliation:
School of Information and Engineering, China University of Mining and Technology Yinchuan College, Yinchuan, 750011, China School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
Zhigang Liu
Affiliation:
School of Information and Engineering, China University of Mining and Technology Yinchuan College, Yinchuan, 750011, China
Miao Wu
Affiliation:
School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
*
*Corresponding author. Email: 63239158@qq.com
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Abstract

The control of dynamic spatial posture for cantilever roadheader is one of the vital problems for intelligent mining, which directly affect the forming quality of cutting tunnel. Therefore, this paper proposed an intelligent optimal combination compensation strategy to adjust the real-time dynamic posture of cantilever roadheader. First, based on the topological structure analysis of cantilever roadheader, the structural loop compensation model for spatial posture deviation was established. Afterward, the principal component analysis (PCA) and multi-objective particle swarm optimization (MPSO) algorithm were applied to improve the analysis speed and accuracy of posture deviation. Finally, parallel dynamic cooperative optimization (PDCO) strategy was combined to achieve the accurate adjusting of posture deviation. The actual experimental and application results indicate that the intelligent optimal combination compensation strategy proposed in the paper can significantly improve the accuracy of the cutting tunnel. The intelligent optimal compensation strategy proposed in this paper transforms the transient spatial posture deviation into structural loop compensation, and implements by parallel cooperative strategy, finally to realize the fast analysis and efficient implementation of spatial dynamic posture deviation for cantilever roadheader during cutting process. The work of this paper provides an effective reference for intelligent deep and remote underground mining, and it can also be applied to effective control of dynamic spatial posture for intelligent engineering machinery products.

Keywords

Cantilever roadheaderDynamic spatial posture deviationOptimal combined compensation strategyPrincipal component analysisMulti-objective particle swarm optimizationParallel dynamic cooperative optimization
Type
Article
Information
Robotica , Volume 40 , Issue 3 , March 2022 , pp. 583 - 598
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

http://www.chinacoal-safety.gov.cn/gk/tzgg/201901/t20190109_223745.shtml Google Scholar
Shaffer, G. K. and Stentz, A., “A Robotic system for underground coal mining,” IEEE International Conference on Robotics and Automation, (1992) pp. 633–638.Google Scholar
Zhao, X. L., Du, X. Y., Qu, X. B. and Li, W. T., “Research on automatic deviation correction technology of cantilever roadheader,” Coal Min. Mach. 31(7), 58–65 (2010).Google Scholar
Liu, G., Mu, D. S., Duan, S. X and Song, D. C., “Design parameters optimization of cutting head of cantilever roadheader based on genetic algorithm,” Appl Mech Mater 215-216, 193–196 (2012). doi: 10.4028/www.scientific.net/AMM.215-216.193 CrossRefGoogle Scholar
Zhai, Y. P., Research on Deviation Compensation Strategy of a New Four DOF Attitude Adjustment Mechanism, Ph.D Thesis (Tianjin University, Tianjin, China, 2015).Google Scholar
Zhang, M. J., Cai, X. H., Lv, F. Y., Zong, K. and Wu, M., “Research on self-correction of grid type roadheader in confined tunnel space,” J. Instrum. 39(3), 62–70 (2018).Google Scholar
Yang, J. J., Tang, Z. H. W., X. L. W and M. Wu, “Study on the stochastic constraint environment modeling of the deviation correction path of coal roadheader,” J. Min. Sci. 4(1), 58–65 (2019).Google Scholar
Ding, X. L., Zhou, L. L. and Zhou, J., “Analysis method of space pose deviation of robot,” J. Beijing Univ. Aeronaut. Astronaut. 35(2), 241–245 (2009).Google Scholar
Zh, M. J., Lu, F. Y., Fu, S. H., Zong, K. and Wu, M., “Study on the pitch angle control of a robotized hydraulic roadheader using different control methods,” J. Mech. Sci. Technol. 32(10), 4893–4901 (2018).Google Scholar
Fang, L. X., Wang, T., Li, Y. M. and Wu, M., “Research on spatial position deviation of cantilever roadheader based on topological structure analysis,” J. Coal Ind. 11, 3940–3951 (2020).Google Scholar
Yang, Y. Y., D. W. J. Dynamics of Mechanical Systems (Tsinghua University Press, Beijing, 2009).Google Scholar
Yang, T. L., Topological Structure Design of Robot Mechanism (Science Press, Beijing, 2012).Google Scholar
Xie, P., Du, Y. H., Tian, P. T. and Liu, B., “A comprehensive error compensation method for parallel robots,” J. Mech. Eng. 48(9), 43–49 (2015).CrossRefGoogle Scholar
Han, X. Z., Zhang, Y. H., Sun, F. J. and Wang, S. H., “Determination method of index weight based on principal component analysis,” J. Sichuan Mil Eng 33(10), 124–126 (2012).Google Scholar
Coello, C. A., Pulido, G. T. and Lechuga, M. S., “Handling Multiple Objectives with Particle Swarm Optimization,” IEEE Transactions on Evolutionary Computation 8(3), (2004).CrossRefGoogle Scholar
Fang, L. X., Wang, T., Wang, P. J., Hou, C. H. and Wu, M., “Kinematic cooperative optimization control algorithm for underground heavy-load robot,” J. Intell. Rob. Syst. (2021). https://doi.org/10.1007/s10846-021-01360-y CrossRefGoogle Scholar
Shanghai peffin Automatic Control Co., Ltd. EPEC PLC set 2 (2024) controller hardware manual (2005).Google Scholar
Xu, G. J., “Research on EPEC controller in control system of roadheader,” Coal Mine Mach. 36(5), 260–261 (2015).Google Scholar
Shichen, F., Yiming, L. I., Kai, Z. O. and Minjun, Z., “Accuracy analyses of UWB pose detection system for roadheader,” Chin. J. Sci. Instrum. 38(8), 1978–1987 (2017).Google Scholar