Xin Chen received the B.S. degree in industrial automation from Central South University of Technology, Changsha, China, in June 1999 and the M.S. degree in control theory and control engineering from Central South University, Changsha, China, in June 2002 and the Ph.D. degree in Mechanical and Electrical Engineering from University of Macau, Faculty of Science and Technology, Macau, in August 2007.
He returned to Central South University as a lecturer in the School of Information Science and Engineering in 2007, and as an associate professor in the School of Information Science and Engineering in Central South University in 2009. He stood out at the Postdoctoral Mobile Station of Control Science and Engineering at Central South University in 2001 and was selected as a doctoral tutor in 2013. In 2014, he moved to China University of Geosciences, Wuhan, China, where he is a professor in the School of Automation. From December 2018 to June 2019, he went to the University of Alberta in Canada as a senior researcher of the National Scholarship Council.
He is the associate dean of the School of Automation, China University of Geosciences (Wuhan), the head of the "Intelligent System Technology" laboratory (717, Information Building). Has been engaged in research in the fields of intelligent control, process control, multi-robot systems, and intelligent equipment. As the first author or corresponding author, he published 86 papers in related fields, including 24 papers in SCI and 62 papers in EI. He applied for 34 invention patents, of which 5 have been authorized, and completed 1 scientific and technological achievement appraisal and 1 industry standard in Hunan Province.
In terms of teaching tasks, he is mainly responsible for teaching undergraduate students "Motion Control System", master students "Machine Learning and Learning Control", doctor students "Intelligent System Technology" and other courses. He also undertook the pilot project of the Ministry of Education's Automation Teaching Steering Committee "Reform and Construction of the Automation Professional Curriculum System for Manufacturing Intelligence and Networking Development Demands", was responsible for revising the 2017 version of the automation professional undergraduate training program, and was responsible for revising the current doctor and master training program.
Professor Chen is a member of IEEE, and he is also a committee member of the Control Theory Professional Committee of the Chinese Automation Society, the Education Working Committee of the Chinese Automation Society, the Youth Working Committee of the Chinese Automation Society, and the Intelligent Air-Space System Professional Committee of the Chinese Artificial Intelligence Society.
The main research interests
(1) Learning control and multi-intelligence systems for non-modeling environments.
1) Multi-layer, distributed decision-control architecture
2) Distributed collaborative learning in a dynamic environment
3) Continuous space Action-Critic self-learning method based on two-phase learning
4) Adaptive dynamic programming method based on reference behavior model
(2) Intelligent system technology and equipment.
1) Intelligent geological drilling equipment
2) Intelligent modeling and control technology for iron and steel metallurgy process
3) High-voltage environment live working robot
4) Music playing robot
 Wu M, Cao W, Chen X. Intelligent Control of Complex Metallurgical Processes. Science Press, 2016.
 Chen X, Wang W, Cao W, et al. Gaussian-kernel-based adaptive critic design using two-phase value iteration[J]. Information Sciences, 2019, 482: 139-155.
 Chen X, Jiao W, Wu M, et al. EID‐Estimation‐Based Periodic Disturbance Rejection for Sintering Ignition Process with Input Time Delay[J]. Asian Journal of Control, 2018, 20(3): 1274-1287.
 Chen X, Cai W, Wu M, et al. A new approach for periodic disturbance rejection in input-time-delay systems[J]. Transactions of the Institute of Measurement and Control, 2018, 40(8): 2589-2598.
 Chen X, Hu J, Wu M, et al. T–S Fuzzy Logic Based Modeling and Robust Control for Burning-Through Point in Sintering Process[J]. IEEE Transactions on Industrial Electronics, 2017, 64(12): 9378-9388.
 Chen X, Chen X.X, Wu M, et al. Modeling and optimization method featuring multiple operating modes for improving carbon efficiency of iron ore sintering process[J]. Control Engineering Practice, 2016, 54: 117-128.
 Chen X, Xie P, He Y, et al. Coordinated learning based on time-sharing tracking framework and Gaussian regression for continuous multi-agent systems[J]. Engineering Applications of Artificial Intelligence, 2015, 41: 56-64.
 Chen X, Xie P, Xiong Y, et al. Two-phase iteration for value function approximation and hyperparameter optimization in gaussian-kernel-based adaptive critic design[J]. Mathematical Problems in Engineering, 2015, 2015.
 Chen X, Li Y. On convergence and parameter selection of an improved particle swarm optimization[J]. International Journal of Control, Automation, and Systems, 2008, 6(4): 559-570.
 Chen X, Li Y. Stability on adaptive NN formation control with variant formation patterns and interaction topologies[J]. International Journal of Advanced Robotic Systems, 2008, 5(1): 8.
 Chen X, Li Y. A modified PSO structure resulting in high exploration ability with convergence guaranteed[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2007, 37(5): 1271-1289.
 Chen X, Li Y. Smooth formation navigation of multiple mobile robots for avoiding moving obstacles[J]. International Journal of Control, Automation, and Systems, 2006, 4(4): 466-479.
 Chen X, Li Y . Neural Network Training Using Stochastic PSO[J]. 2006.
 Chen X, Li Y. Cooperative transportation by multiple mobile manipulators using adaptive NN control[C]//The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, 2006: 4193-4200.
 Zhou K, Chen X*, Wu M, et al. A new hybrid modeling and optimization algorithm for improving carbon efficiency based on different time scales in sintering process[J]. Control Engineering Practice, 2019, 91: 104104.
 Wang W, Chen X*, Fu H, et al. Data-driven adaptive dynamic programming for partially observable nonzero-sum games via Q-learning method[J]. International Journal of Systems Science, 2019: 1-15.
 Wang W, Chen X*. Model-free optimal containment control of multi-agent systems based on actor-critic framework[J]. Neurocomputing, 2018, 314: 242-250.
 Chen XX, Chen X*, She J, et al. A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process[J]. Neurocomputing, 2017, 249: 128-139.
 Chen XX, Chen X*, She J, et al. Hybrid multistep modeling for calculation of carbon efficiency of iron ore sintering process based on yield prediction[J]. Neural Computing and Applications, 2017, 28(6): 1193-1207.
 Chen XX, Chen X*, She J, et al. A hybrid just-in-time soft sensor for carbon efficiency of iron ore sintering process based on feature extraction of cross-sectional frames at discharge end[J]. Journal of Process Control, 2017, 54: 14-24.
 Wang F, Chen X*, He Y, et al. Finite‐time consensus problem for second‐order multi‐agent systems under switching topologies[J]. Asian Journal of Control, 2017, 19(5): 1756-1766.
 Li Y, Chen X*. Modeling and simulation of swarms for collecting objects[J]. Robotica, 2006, 24(3): 315-324.
 Li Y, Chen X*. A new stochastic PSO technique for neural network training[C]//International Symposium on Neural Networks. Springer, Berlin, Heidelberg, 2006: 564-569.
 Li Y, Chen X*. Mobile robot navigation using particle swarm optimization and adaptive NN[C]//International Conference on Natural Computation. Springer, Berlin, Heidelberg, 2005: 628-631.
 Li Y, Chen X*. Formation control for a multiple robotic system using adaptive neural network[C]//International Symposium on Neural Networks. Springer, Berlin, Heidelberg, 2005: 228-233.