陆新江 - 中南大学 - 机电工程学院

个人简介

教育背景 2005-2010 博士香港城市大学制造工程与工程管理系 2002-2005 硕士中南大学机电工程学院 1998-2002 本科中南大学机电工程学院工作经历 2010-至今中南大学机电工程学院 2005.2-2005.7 香港城市大学深圳研究院

研究领域

机器人理论与技术机器学习理论与技术智能控制理论与技术机器视觉与智能装备理论与技术可靠性与稳健性设计理论与应用

近期论文

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Lu X.J., Ming L., Liu W.B., Li H.X., Probabilistic Regularized Extreme Learning Machine for Robust Modeling of Noise data, IEEE Transactions on Cybernetics, vol.48, no.8, pp. 2368-2377, 2018. Lu X.J., Liu W.B., Zhou C., Huang M.H., Robust Least Squares Support Vector Machine with minimization of mean and variance of modeling error, IEEE Transactions on Neural Networks and Learning Systems, vol.29, no.7, pp.2909-2920, 2018. Sui H., Lu X.J. Nonlinear dynamic analysis of complex hydraulic driving processes, Journal of Sound and Vibration, vol.430, pp.115-133, 2018. Qin G.F., Lu X.J., Integration of Weighted LS-SVM and Manifold Learning for Fuzzy Modeling, Neurocomputing, 282, pp.184-191, 2018. Lu X.J., Zou W., Huang M.H. (2017), Robust Spatiotemporal LS-SVM Modeling for Nonlinear Distributed Parameter System with Disturbance, IEEE Trans. on Industrial Electronics, 64 (10), pp. 8003 – 8012, 2017. Lu X.J., Yin F., Liu C, Huang M.H. （2017）, Online Spatiotemporal Extreme Learning Machine for Complex Time-Varying Distributed Parameter Systems，IEEE Transactions on Industrial Informatics, 13(4), pp. 1753 – 1762, 2017. Lu X.J., Liu W, Zhou C, Huang M.H.（2017）, Probabilistic Weighted Support Vector Machine for Robust Modeling with Application to Hydraulic Actuator. IEEE Transactions on Industrial Informatics, 13(4), pp. 1723 – 1733, 2017. Lu X.J., Zou W., Huang M.H.,（2016） A Novel Spatiotemporal LS-SVM Method for Complex Distributed Parameter Systems with Applications to Curing Thermal Process, IEEE Transactions on Industrial Informatics, 12(3), pp.1156 - 1165, 2016. Lu X.J., Zhou C., Huang M.H., Lv W.B (2016). Regularized online sequential extreme learning machine with adaptive regulation factor for time-varying nonlinear system, Neurocomputing, 174，pp.617-626, 2016. Lu X.J., Liu C., Huang M.H. (2015). Online Probabilistic Extreme Learning Machine for Distribution Modeling of Complex Batch Forging Processes, IEEE Transactions on Industrial Informatics, 11(6), pp.1277-1286, 2015. Lu X.J., Zou W., Huang M.H (2015). An adaptive modeling method for time varying distributed parameter processes with curing process applications, Nonlinear Dynamics, 82(1), pp. 865-876, 2015 Lu X.J., Fan B., Huang, M.H. (2015). A Novel LS-SVM Modeling Method for a Hydraulic Press Forging Process with Multiple Localized Solutions, IEEE Transactions on Industrial Informatics, 11(3), pp.663-670, 2015. Lu X.J. , Zou W., Huang M.H., Deng K. (2015). A process/shape-decomposition modeling method for deformation force estimation in complex forging processes, International Journal of Mechanical Sciences, 90, pp.190-199, 2015. Lu X.J. , Li H.X., Huang M.H. (2014) . Stability and robust design using a sector nonlinearity approach for nonlinear manufacturing systems, Mechanism and Machine Theory, 82, pp. 115-127, 2014. Lu, X.J. & Huang, M.H. (2013). Nonlinear-Measurement-Based Integrated Robust Design and Control for Manufacturing System, IEEE Trans. on Industrial Electronics, 60(7), pp.2711-2720, 2013. Lu, X.J. & Huang, M.H. (2013). Multi-domain modeling based robust design for nonlinear manufacture system, International Journal of Mechanical Sciences, 75, pp.80-86, 2013.