科研方向
自动化技术发展水平已成为衡量一个国家现代化程度的重要指标,从航空航天到大规模工业生产,从智能制造到供应链管理,从智能交通到智慧城市,从智能电网到智慧能源,从医疗仪器到家庭服务,自动化技术在提高生产效率的同时,也使我们的生活变得更加美好。南方科技大学控制科学与工程学科主要涵盖如下三个自动化领域的研究方向:(1)控制理论与控制工程,(2)智能感知与自主控制,(3) 模式识别与机器人控制.
1. 控制理论与控制工程
控制理论面临着被控系统越来越复杂、性能要求越来越苛刻的挑战。该方向的研究人员通过设计新的建模与辨识、分析与综合、自适应与优化先进技术来应对挑战。该方向的理论研究成果在航空航天、制造业、新能源等行业有广泛应用。
研究方向:全驱动系统控制、复杂系统相论、分布式控制与估计、网络化系统控制与优化、航天航空器控制.
参与教授:段广仁、丘立、付敏跃、田玉平、刘涛、徐翔.
2. 智能感知与自主控制
实际系统所处的环境十分复杂,并受不确定性的极大影响。自动控制面临着前所未有的挑战,尤其是在信息物理系统中。该方向聚焦智能感知和自主控制的新理论、先进算法和创新技术,突破控制科学和人工智能技术的壁垒。其工业应用涵盖智能制造、集群无人系统、物联网等。
研究方向:网络化控制、多智能体系统、智能学习控制、信息物理系统智能感知与控制.
参与教师:刘国平、林志赟、杨再跃、孔贺、陈亮名.
3. 模式识别与机器人控制
模式识别是指对数据中的模式和规律性的自动识别,研究成果在图像处理与计算机视觉、大数据分析、生物信息学、自然语言处理、类脑智能、机器人等领域有广泛的应用。机器人控制将机器人作为研究对象,以数学、力学、机械、控制、传感、人工智能等理论为基础,研究机器人在复杂动态环境中的态势感知、任务分配、运动规划、导航与制导、运动控制等技术。
研究方向:机器人感知与智能、机器人视觉、人工智能、航天系统、无人系统、智能医学、物联网.
参与教师:刘德荣、孟庆虎、张宏、张巍、丁克蜜.
科研成果
出版著作:
[1] D. Liu, Q. Wei, D. Wang, X. Yang, and H. Li, Adaptive Dynamic Programming with Applications in Optimal Control. Springer, 2017.
[2] G. R. Duan, Generalized Sylvester Equations – Unified Parametric Solutions. CRC Press, 2015.
[3] G. R. Duan, Analysis and Design of Descriptor Linear Systems. Springer, 2013.
[4] G. R. Duan and H. H. Yu, LMIs in Control Systems – Analysis, Design and Applications. CRC Press, 2013.
[5] Y. P. Tian, Frequency-Domain Analysis and Design of Distributed Control Systems. Wiley, 2012.
[6] L. Qiu and K. Zhou, Introduction to Feedback Control. Prentice-Hall, 2009.
[7] G. P. Liu, Nonlinear Identification and Control: A Neural Network Approach. Springer-Verlag, 2001.
[8] G. P. Liu and R. J. Patton, Eigenstructure Assignment for Control System Design. Wiley, 1998.
[9] G. R. Duan, Linear Control System Theory. HIT Press (1st ed.), 1996; HIT Press (2nd ed.), 2004; Science Press of China (3rd ed.), 2016.
[10] D. Liu and A. N. Michel, Dynamical Systems with Saturation Nonlinearities: Analysis and Design. Springer-Verlag, 1994.
部分期刊论文:
[1] L. Chen, L. Xie, X. Li, X. Fang, and M. Feroskhan, “Simultaneous localization and formation using angle-only measurements in 2D,” Automatica, vol. 146, Dec. 2022, Art. no. 110605.
[2] X. Xu, L. Liu, and G. Feng, “Lyapunov characterizations on input-to-state of infinite-delayed systems,” Automatica, vol. 146, Dec. 2022, Art. no. 110585.
[3] L. Chen, Q. Yang, M. Shi, Y. Li, and M. Feroskhan, “Stabilizing angle rigid formations with prescribed orientation and scale,” IEEE Trans. Industrial Electronics, vol. 69, no. 11, pp. 11654–11664, Nov. 2022.
[4] D. Zhao, S. Z. Khong, and L. Qiu, “System monotonicity and identification: A geometric perspective of the Frisch-Shapiro scheme,” IEEE Trans. Automatic Control, vol. 67, no. 11, Nov. 2022.
[5] L. Chen, “Triangular angle rigidity for distributed localization in 2D,” Automatica, vol. 143, Sept. 2022, Art. no. 110414.
[6] Y. Mo, W. Chen, S. Z. Khong, and L. Qiu, “A structure-tensor approach to integer matrix completion in indivisible resource allocation,” IEEE Trans. Automatic Control, vol. 67, no. 9, pp. 4541– 4554, Sept. 2022.
[7] C. Yao, S. Chen and Z. Yang, “Joint routing and charging problem of multiple electric vehicles: A fast optimization algorithm,” IEEE Trans. Intelligent Transportation Systems, vol. 23, no. 9, pp. 8184–8193, Sept. 2022.
[8] T. Liu and J. Huang, “Global exponential estimation of the unknown frequencies of discrete-time multi-tone sinusoidal signals,” Automatica, vol. 142, Aug. 2022, Art. no. 110377.
[9] X. Mao, W. Chen, and L. Qiu, “Phases of discrete-time LTI multivariable systems,” Automatica, vol. 142, Aug. 2022, Art. no. 110311.
[10] L. Chen, Z. Lin, H. Garcia de Marina, Z. Sun, and M. Feroskhan, “Maneuvering angle rigid formations with global convergence guarantees,” IEEE/CAA J. Automatica Sinica, vol. 9, no. 8, pp. 1464–1475, Aug. 2022.
[11] L. Chen and Z. Sun, “Gradient-based bearing-only formation control: An elevation angle approach,” Automatica, vol. 141, Jul. 2022, Art. no. 110310.
[12] L. Chen, K. Cao, L. Xie, X. Li, and M. Feroskhan, “3-D network localization using angle measurements and reduced communication,” IEEE Trans. Signal Processing, vol. 70, no. 4, pp. 2404–2415, Apr. 2022.
[13] Y. Lin, Z. Lin, Z. Sun, and B. D. O. Anderson, “A unified approach for finite-time global stabilization of affine, rigid, and translational formation,” IEEE Trans. Automatic Control, vol. 67, no. 4, pp. 1869–1881, Apr. 2022.
[14] L. Chen, H. Garcia de Marina, and M. Cao, “Maneuvering formations of mobile agents using designed mismatched angles,” IEEE Trans. Automatic Control, vol. 67, no. 4, pp. 1655–1668, Apr. 2022.
[15] J. Sun, T. Chen, G. Giannakis, Q. Yang, and Z. Yang, “Lazily aggregated quantized gradient innovation for communication-efficient federated learning,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 44, no. 4, pp. 2031–2044, Apr. 2022.
[16] G. P. Liu, “Coordination of networked nonlinear multi-agents using a high-order fully actuated predictive control strategy,” IEEE/CAA J. Automatica Sinica, vol. 9, no. 4, pp. 615–623, Apr. 2022.
[17] Z. Guo, P. Pinson, S. Chen, Q. Yang, and Z. Yang, “An asynchronous online negotiation mechanism for real-time peer-to-peer electricity markets,” IEEE Trans. Power Systems, vol. 37, no. 3, pp. 1868–1880, Mar. 2022.
[18] G. P. Liu, “Coordinated control of networked multi-agent systems via distributed cloud computing using multi-step state predictors,” IEEE Trans. Cybernetics, vol. 52, no. 2, pp. 810–820, Feb. 2022.
[19] X. Xu, L. Liu, M. Krstic, and G. Feng, “Stability analysis and predictor feedback control for systems with unbounded delays,” Automatica, vol.135, Jan. 2022, Art. no. 109958.
[20] W. Liu, S. Chen, Y. Hou, and Z. Yang, “Trilevel mixed integer optimization for day-ahead spinning reserve management of electric vehicle aggregator with uncertainty,” IEEE Trans. Smart Grid, vol. 13, no. 1, pp. 613–625, Jan. 2022.
[21] H. Kong, M. Shan, S. Sukkarieh, T. Chen, and W. X. Zheng, “Kalman filtering under arbitrary unknown inputs and norm constraints,” Automatica, vol. 133, Nov. 2021, Art. no. 109871.
[22] B. Yang, J. Li, and H. Zhang, “Resilient indoor localization system based on UWB and visual-inertial sensors for complex environments,” IEEE Trans. Instrumentation and Measurements, vol. 70, Aug. 2021, Art. no. 8504014.
[23] L. Chen, M. Cao, and C. Li, “Angle rigidity and its usage to stabilize multi-agent formations in 2-D,” IEEE Trans. Automatic Control, vol. 66, no. 8, pp. 3667–3681, Aug. 2021.
[24] K. Ding, X. Ren, H. Qi, G. Shi, X. Wang, and L. Shi. “Interference game for intelligent sensors in cyber–physical systems,” Automatica, vol. 129, Jul. 2021, Art. no. 110311.
[25] Y. Wu, K. Ding, Y. Li, and L. Shi, “Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability,” Automatica, vol. 128, Jun. 2021, Art. no. 109568.
[26] J. Wang, J. Liu, W. Chen, W. Chi, and M. Q. H. Meng, “Robot path planning via neural-network-driven prediction,” IEEE Trans. Artificial Intelligence, vol. 3, no. 3, pp. 451–460, Jun. 2021.
[27] L. Huang, K. Ding, A. S. Leong, D. E. Quevedo, and L. Shi, “Encryption schedules for remote state estimation under an operation constraint,” Automatica, vol. 127, May 2021, Art. no. 109537.
[28] W. Chen, D. Wang, J. Liu, Y. Chen, S. Z. Khong, T. Basar, K. H. Johansson, and L. Qiu, “On spectral properties of signed Laplacians with connections to eventual positivity,” IEEE Trans. Automatic Control, vol. 66, no. 5, pp. 2177–2190, May 2021.
[29] D. Su, H. Kong, S. Sukkarieh, and S. Huang, “Necessary and sufficient conditions for observability of SLAM-based TDOA sensor array calibration and source localization,” IEEE Trans. Robotics, vol. 37, no. 5, pp. 1451–1468, May 2021. 26
[30] Z. Guo, P. Pinson, S. Chen, Q. Yang, and Z. Yang, “Online optimization for real-time peer-to-peer electricity market mechanisms,” IEEE Trans. Smart Grid, vol. 12, no. 5, pp. 4151–4163, May 2021.
[31] W. Liu, S. Chen, Y. Hou, and Z. Yang, “Optimal reserve management of electric vehicle aggregator: Discrete bilevel optimization model and exact algorithm,” IEEE Trans. Smart Grid, vol. 12, no. 5, pp. 4003–4015, May 2021.
[32] T. Liu and J. Huang, “Discrete-time distributed observers over jointly connected switching networks and an application,” IEEE Trans. Automatic Control, vol. 66, no. 4, pp. 1918–1924, Apr. 2021.
[33] J. Wang and M. Q. H. Meng, “Real-time decision making and path planning for robotic autonomous luggage trolley collection at airports,” IEEE Trans. Systems, Man, and Cybernetics: Systems, vol. 52, no. 4, pp. 2174–2183, Apr. 2021.
[34] M. Shakeri, S. Y. Loo, H. Zhang, and K. Hu, “Polarimetric monocular dense mapping using relative deep depth prior,” IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 4512–4519, Mar. 2021.
[35] D. Zhao, S. Z. Khong, and L. Qiu, “Stabilization of cascaded two-port networked systems with simultaneous nonlinear uncertainties,” Automatica, vol. 123, Jan. 2021, Art. no. 109360.
[36] K. Ding, J. Wu, and L. Xie, “Minimum-degree distributed graph filter design,” IEEE Trans. Signal Processing, vol. 69, no. 1, pp. 1083–1096, Jan. 2021.
[37] K. Ding, X. Ren, A. S. Leong, D. E. Quevedo, and L. Shi, “Remote state estimation in the presence of an active eavesdropper,” IEEE Trans. Automatic Control, vol. 66, no. 1, pp. 229–244, Jan. 2021.
[38] T. Yu, D. Zhao, and L. Qiu, “Networked robust stability for LTV systems with simultaneous uncertainties in plant, controller and communication channels,” SIAM J. Control and Optimization, vol. 59, pp. 1–23, Jan. 2021.
[39] Y. P. Tian, S. Chun, G. Chen, S. Zong, Y. Huang, and B. Wang, “Delay compensation based time synchronization under random delays: Algorithm and experiment,” IEEE Trans. Control Systems Technology, vol. 29, no. 1, pp. 80–95, Jan. 2021.
[40] Z. Guo, P. Pinson, S. Chen, Q. Yang, and Z. Yang, “Chance-constrained peer-to-peer joint energy and reserve market considering renewable generation uncertainty,” IEEE Trans. Smart Grid, vol. 12, no. 1, pp. 798–809, Jan. 2021.
[41] K. Ding, and J. Zhang, “Multi-party privacy conflict management in online social network: A network game perspective,” IEEE/ACM Trans. Networking, vol. 28, no. 6, pp. 2685–2698, Dec. 2020.
[42] J. Wang and M. Q.-H. Meng, “Optimal path planning using generalized Voronoi Graph and multiple potential functions,” IEEE Trans. Industrial Electronics, vol. 67, no. 12, pp. 10621–10630, Dec. 2020.
[43] L. Chen, J. Mei, C. Li, and G. Ma, “Distributed leader-follower affine formation maneuver control for high-order multiagent systems,” IEEE Trans. Automatic Control, vol. 65, no. 11, pp. 4941– 4948, Nov. 2020.
[44] X. Xu, L. Liu, and G. Feng, “Stability and stabilization of infinite delayed systems: A Lyapunov based method,” IEEE Trans. Automatic Control, vol. 65, no. 11, pp. 4509–4524, Nov. 2020.
[45] G. P. Liu, “Coordinated control of networked multi-agent systems with communication constraints using a proportional integral predictive control strategy,” IEEE Trans. Cybernetics, vol. 50, no. 11, pp. 4735–4743, Nov. 2020.
[46] G. P. Liu, “Predictive control of networked nonlinear multi-agent systems with communication constraints,” IEEE Trans. Systems, Man, and Cybernetics: Systems, vol. 50, no. 11, pp. 4447–4457, Nov. 2020. 27
[47] J. Sun, M. Chen, H. Liu, Q. Yang, and Z. Yang, “Workload transfer strategy of urban neighboring data centers with market power in local electricity market,” IEEE Trans. Smart Grid, vol. 11, no. 4, pp. 3083–3094, Nov. 2020.
[48] H. Kong, M. Shan, D. Su, Y. Qiao, A. Al-Azzawi, and S. Sukkarieh, “Filtering for systems subject to unknown inputs without a priori initial information,” Automatica, vol. 120, Oct. 2020, Art. no. 109122.
[49] X. Xu, L. Liu, and G. Feng, “On Lipschitz conditions of infinite dimensional systems,” Automatica, vol. 117, Jul. 2020, Art. no. 108947.
[50] Y. Mo, W. Chen, L. Qiu, and P. Varaiya, “Market implementation of multiple-arrival multiple-deadline differentiated energy services,” Automatica, vol. 116, Jun. 2020, Art. no. 108933.
[51] J. Wang, M. Q. H. Meng, and O. Khatib, “EB-RRT: Optimal motion planning for mobile robots,” IEEE Trans. Automation Science and Engineering, vol. 17, no. 4, pp. 2063–2073, Apr. 2020.
[52] J. Wang, W. Chi, C. Li, C. Wang, and M. Q. H. Meng, “Neural RRT*: Learning-based optimal path planning,” IEEE Trans. Automation Science and Engineering, vol. 17, no. 4, pp. 1748–1758, Apr. 2020.
[53] H. Xiong, Y. Chi, B. Hu, and W. Zhang, “Analytical convergence regions of accelerated gradient descent in nonconvex optimization under regularity condition,” Automatica, vol. 113, Mar. 2020, Art. no. 108715.
[54] K. Ding, X. Ren, D. E. Quevedo, S. Dey, and L. Shi, “Defensive deception against reactive jamming attacks in remote state estimation,” Automatica, vol. 113, Mar. 2020, Art. no. 108680.
[55] D. Zhao, L. Qiu, and G. Gu, “Stabilization of two-port networked systems with simultaneous uncertainties in plant, controller, and communication channels,” IEEE Trans. Automatic Control, vol. 65, no. 3, pp. 1160–1175, Mar. 2020.
[56] S. Chen, Z. Guo, Z. Yang, J. Xu, and R. Cheng, “A game theoretic approach to phase balancing by plug-in electric vehicles in the smart grid,” IEEE Trans. Power Systems, vol. 35, no. 3, pp. 2232–2244, Mar. 2020.
[57] X. Xu, L. Liu, and G. Feng, “Consensus of linear multi-agent systems with distributed infinite transmission delays: A low gain method,” IEEE Trans. Automatic Control, vol. 65, no. 2, pp. 809–816, Feb. 2020.
[58] Z. Guo, S. Chen, H. Liu, Q. Yang, and Z. Yang, “A fast algorithm for optimal power scheduling of large-scale appliances with temporally-spatially coupled constraints,” IEEE Trans. Smart Grid, vol. 11, no. 2, pp. 1136–1146, Feb. 2020.
[59] S. Li, W. Zhang, and L. Zhao, “Connections between mean-field game and social welfare optimization,” Automatica, vol. 110, Dec. 2019, Art. no. 108590.
[60] T. Liu and J. Huang, “Cooperative robust output regulation for a class of nonlinear multi-agent systems subject to a nonlinear leader system,” Automatica, vol. 108, Oct. 2019, Art. no. 108501.
[61] H. Kong and S. Sukkarieh, “An internal model approach to estimation of systems with arbitrary unknown inputs,” Automatica, vol. 108, Oct. 2019, Art. no. 108482.
[62] T. Liu and J. Huang, “Robust output regulation of discrete-time linear systems by quantized output feedback control,” Automatica, vol. 107, pp. 587–590, Sept. 2019.
[63] X. Xu, L. Liu, and G. Feng, “Semi-global stabilization of linear systems with distributed infinite input delays and actuator saturations,” Automatica, vol. 107, pp. 398–405, Sept. 2019.
[64] Q. Liu, W. Chen, Z. Wang, and L. Qiu, “Stabilization of MIMO systems over multiple independent and memoryless fading noisy channels,” IEEE Trans. Automatic Control, vol. 64, no. 4, pp. 1581– 1594, Apr. 2019.
[65] T. Liu and J. Huang, “A distributed observer for a class of nonlinear systems and its application to a leader-following consensus problem,” IEEE Trans. Automatic Control, vol. 64, no. 3, pp. 1221– 1227, Mar. 2019. 28
[66] L. He, N. Ray, Y. Guan, and H. Zhang, “Fast large-scale spectral clustering via explicit feature mapping,” IEEE Trans. Cybernetics, vol. 49, no. 3, pp. 1058–1071, Mar. 2019.
[67] Z. Han, K. Guo, L. Xie, and Z. Lin, “Integrated relative localization and leader-follower formation control,” IEEE Trans. Automatic Control, vol. 64, no. 1, pp. 20–34, Jan. 2019.
[68] H. Kong and S. Sukkarieh, “Suboptimal receding horizon estimation via noise blocking,” Automatica, vol. 98, pp. 66–75, Dec. 2018.
[69] T. Liu and J. Huang, “Adaptive cooperative output regulation of discrete-time linear multi-agent systems by a distributed feedback control law,” IEEE Trans. Automatic Control, vol. 63, no. 12, pp. 4383–4390, Dec. 2018.
[70] L. Zhao and W. Zhang, “A unified stochastic hybrid system approach to aggregated load modeling for demand response,” IEEE Trans. Automatic Control, vol. 63, no. 12, pp. 4250–4263, Dec. 2018.
[71] H. Kong and S. Sukkarieh, “Metamorphic moving horizon estimation,” Automatica, vol. 97, pp. 167–171, Nov. 2018.
[72] X. Xu, L. Liu, and G. Feng, “Stabilization of linear systems with distributed infinite input delays: A low gain approach,” Automatica, vol. 94, pp. 396–408, Aug. 2018.
[73] T. Liu and J. Huang, “Leader-following attitude consensus of multiple rigid body systems subject to jointly connected switching networks,” Automatica, vol. 92, pp. 63–71, Jun. 2018.
[74] Y. P. Tian, X. J. Sun, and O. Tian, “Detection performance of the majority dominance rule in m-ary relay trees with node and link failures,” IEEE Trans. Signal Processing, vol. 66, no. 6, pp. 1469– 1482, Jun. 2018.
[75] T. Liu and J. Huang, “A discrete-time recurrent neural network for solving rank-deficient matrix equations with an application to output regulation of linear systems,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 6, pp. 2271–2277, Jun. 2018.
[76] K. Ding, X. Ren, D. E. Quevedo, S. Dey, and L. Shi. “DoS attacks on remote state estimation with asymmetric information,” IEEE Trans. Control of Network Systems, vol. 6, no. 2, pp. 653–666, Jun. 2018.
[77] T. Liu and J. Huang, “Cooperative output regulation for a class of nonlinear multi-agent systems with unknown control directions subject to switching networks,” IEEE Trans. Automatic Control, vol. 63, no. 3, pp. 783–790, Mar. 2018.
[78] X. Xu, L. Liu, and G. Feng, “Consensus of discrete-time linear multiagent systems with communication, input and output delays,” IEEE Trans. Automatic Control, vol. 63, no. 2, pp. 492–497, Feb. 2018.
[79] H. Foroughi, N. Ray, and H. Zhang, “Object classification with joint projection and low-rank dictionary learning,” IEEE Trans. Image Processing, vol. 27, no. 2, pp. 806–821, Feb. 2018.
[80] Y. P. Tian, “Time synchronization in WSNs with random bounded communication delays,” IEEE Trans. Automatic Control, vol. 62, no. 10, pp. 5445–5450, Oct. 2017.
[81] G. P. Liu, “Predictive control of networked multi-agent systems via cloud computing, IEEE Trans. Cybernetics, vol. 47, no. 8, pp. 1852–1859, Aug. 2017.
[82] H. Chen and W. Zhang, “On weak topology for optimal control of switched nonlinear systems,” Automatica, vol. 81, pp. 409–415, Jul. 2017.
[83] K. Ding, Y. Li, D. E. Quevedo, S. Dey, and L. Shi. “A multi-channel transmission schedule for remote state estimation under DoS attacks,” Automatica, vol. 78, pp. 194–201, Apr. 2017.
[84] G. P. Liu, “Consensus and stability analysis of networked multi-agent predictive control,” IEEE Trans. Cybernetics, vol. 47, no. 4, pp. 1114–1119, Apr. 2017.
[85] Y. Lu and W. Zhang, “A piecewise smooth control-Lyapunov function framework for switching stabilization,” Automatica, vol. 76, pp. 258–265, Feb. 2017.
[86] Y. Lu and W. Zhang, “On switching stabilizability for continuous-time switched linear systems,” IEEE Trans. Automatic Control, vol. 61, no. 11, pp. 3515–3520, Nov. 2016.
[87] Z. Lin, L. Wang, Z. Chen, M. Fu, and Z. Han, “Necessary and sufficient graphical conditions for affine formation control,” IEEE Trans. Automatic Control, vol. 61, no. 10, pp. 2877–2891, Oct. 2016. 29
[88] M. Deghat, B. D. O. Anderson, and Z. Lin, “Combined flocking and distance-based shape control of multi-agent formation,” IEEE Trans. Automatic Control, vol. 61, no. 7, pp. 1824–1837, Jul. 2016.
[89] Z. Lin, L. Wang, Z. Han, and M. Fu, “A graph Laplacian approach to coordinate-free formation stabilization for directed networks,” IEEE Trans. Automatic Control, vol. 61, no. 5, pp. 1269–1280, May 2016.
[90] C. Chang and W. Zhang, “Distributed control of inverter-based lossy microgrids for power sharing and frequency regulation under voltage constraints,” Automatica, vol. 66, pp. 85–95, Apr. 2016.
[91] C. Lin, Z. Lin, R. Zheng, G. Yan, and G. Mao, “Distributed source localization of multi-agent systems with bearing angle measurements,” IEEE Trans. Automatic Control, vol. 61, no. 4, pp. 1105– 1110, Apr. 2016.
[92] Y. P. Tian, S. Zong, and Q. Cao, “Structural modeling and convergence analysis of consensus-based time synchronization algorithms over networks: Non-topological conditions,” Automatica, vol. 65, pp. 64–75, Mar. 2016.
[93] D. Liu, X. Yang, D. Wang, and Q. Wei, “Reinforcement-learning-based robust controller design for continuous-time uncertain nonlinear systems subject to input constraints,” IEEE Trans. Cybernetics, vol.45, no.7, pp.1372–1385, Jul. 2015.
[94] Z. Lin, L. Wang, Z. Han, and M. Fu, “Distributed formation control of multi-agent systems using complex Laplacian,” IEEE Trans. Automatic Control, vol. 59, no. 7, pp. 1765–1777, Jul. 2014.
[95] D. Liu and Q. Wei, “Policy iteration adaptive dynamic programming algorithm for discrete-time nonlinear systems,” IEEE Trans. Neural Networks and Learning Systems, vol. 25, no. 3, pp. 621– 634, Mar. 2014.
[96] Y. P. Tian and Q. Wang, “Global stabilization of rigid formations in the plane,” Automatica, vol. 49, no. 5, pp. 1436–1441, May 2013.
[97] D. Liu and Q. Wei, “Finite-approximation-error-based optimal control approach for discrete-time nonlinear systems,” IEEE Trans. Cybernetics, vol. 43, no. 2, pp. 779–789, Apr. 2013.
[98] Y. P. Tian and Y. Zhang, “High-order consensus of heterogeneous multi-agent systems with unknown communication delays,” Automatica, vol. 48, no. 6, pp. 1205–1212, Jun. 2012.
[99] W. Zhang, M. Kamgarpour, D. Sun, and C. Tomlin, “A hierarchical flight planning framework for air traffic management,” Proc. IEEE, vol. 100, no. 1, pp. 179–194, Jan. 2012.
[100] Y. Lan, G. Yan, and Z. Lin, “Synthesis of distributed control for coordinated path following based on hybrid control,” IEEE Trans. Automatic Control, vol. 56, no. 5, pp. 1170–1175, May 2011.
[101] G. P. Liu, “Predictive controller design of networked systems with communication delays and data loss,” IEEE Trans. Circuits and Systems II, vol. 57, no. 6, pp. 481–485, Jun. 2010.
[102] W. Zhang, A. Abate, J. Hu, and M. Vitus, “Exponential stabilization of discrete-time switched linear systems,” Automatica, vol. 45, no. 11, pp. 2526–2536, Nov. 2009.
[103] Y. P. Tian and C. L. Liu, “Robust consensus of multi-agent systems with diverse input delays and asymmetric interconnection perturbations,” Automatica, vol. 45, no. 5, pp. 1347–1353, May 2009.
[104] Y. P. Tian and C. L. Liu, “Consensus of multi-agent systems with diverse input and communication delays,” IEEE Trans. Automatic Control, vol. 53, no. 9, pp. 2122–2128, Oct. 2008.
[105] D. Liu, H. Javaherian, O. Kovalenko, and T. Huang, “Adaptive critic learning techniques for engine torque and air-fuel ratio control,” IEEE Trans. Systems, Man and Cybernetics-Part B: Cybernetics, vol. 38, no. 4, pp. 988–993, Aug. 2008.
[106] D. Liu and Y. Cai, “Taguchi method for solving the economic dispatch problem with nonsmooth cost functions,” IEEE Trans. Power Systems, vol. 20, no. 4, pp. 2006–2014, Nov. 2005.
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科研项目
丘立 (PI),A phase theory for nonlinear systems, Hong Kong Research Grants Council General Research Fund, 2022.7.1–2024.6.30.
段广仁 (PI),高阶全驱系统理论与航天器控制技术,国家自然科学基金委基础科学中心项目,2022.1.1–2026.12.31. 31
林志赟 (PI),多智能体非线性协调控制与估计问题研究,国家自然科学基金面上项目,2022.1.1–2025.12.31.
孔贺 (PI),机器人系统的智能感知与决策,国家自然科学基金优秀青年科学基金项目(海外),2022.1.1–2024.12.31.
丘立 (PI),Synchronization of diverse dynamic agents with uniform network controllers, Hong Kong Research Grants Council General Research Fund, 2022.1.1–2024.12.31.
田玉平 (PI),噪声环境下无线传感器网络协作时空感知方法研究,国家自然科学基金面上项目,2021.1.1–2024.12.31.
刘德荣 (PI),考虑未知时滞的非线性系统固定时间自适应动态规化控制方法,国家自然科学基金面上项目,2021.1.1–2024.12.31. 张巍 (PI),模型机理与数据驱动相结合的混杂系统最优控制理论与应用研究,国家自然科学基金面上项目,2021.1.1–2024.12.31. 孟庆虎 (PI),Development of a state-of-the-art augmented-reality surgical navigation system for minimally invasive surgery, Hong Kong Research Grants Council General Research Fund, 2021.1.1– 2023.12.31.
丘立 (PI),Network small phase theorem, Hong Kong Research Grants Council General Research Fund, 2021.1.1–2023.12.31.
田玉平 (PI),多源噪声环境中时空敏感群体的合作感知与适应性协同,浙江省自然科学基金重点项目,2021.1.1–2023.12.31.
张巍 (PI),基于传动安全控制的机器人关节伺服关键技术研究,深圳市基础研究重点项目,2020.4.1–2023.10.31.
丘立 (PI),Phase – A missing component in MIMO and network system analysis, Hong Kong Research Grants Council General Research Fund, 2020.1.1–2022.12.31.
孟庆虎 (PI),A robotic wireless capsule endoscopic system for automated gastrointestinal disease diagnosis, Hong Kong Research Grants Council General Research Fund, 2019.6.1–2022.5.31.
杨再跃 (PI),基于大规模分布式微储能的智能电网辅助服务:架构与算法,国家自然科学基金面上项目,2019.1.1–2022.12.31.
张宏 (PI),Centre for autonomous systems in strengthening future communities, Alberta Economic Development and Trade of Canada, 2018.1.1–2024.12.31.
张宏 (PI),移动机器人SLAM适应性和可扩展性提升及其产业化,广东省“珠江人才计划”领军人才,2017.7.16–2023.7.15.
段广仁 (PI),空间翻滚目标捕获过程中的航天器控制理论与方法,国家自然科学基金重大项目,2017.1.1–2021.12.31.
张巍 (PI),CAREER: Hierarchical control of large-scale cyber-physical systems, National Science Foundation of USA, 2016.8.1–2021.7.31.
刘德荣 (PI),基于数据的建筑群及分布式能源系统一体化建模与自学习优化控制,国家自然科学基金重点项目,2016.1.1–2020.12.31.
张宏 (PI),基于SLAM的自主移动机器人关键技术的研究及产业化,广东省前沿与关键技术创新专项资金(省重大科技专项),2016.1.1–2019.12.31.
刘国平 (PI),航天器组网与编队过程中的协调控制方法及应用,国家自然科学基金重点项目,2014.1.1–2018.12.31.
刘德荣 (PI),基于数据的非线性控制系统分析与设计,国家自然科学基金重点项目,2011.1.1–2014.12.31.
段广仁 (PI),航天飞行器的鲁棒控制理论与应用,国家自然科学基金创新研究群体项目,2010.1.1–2016.12.31.
刘德荣 (PI),智能控制理论,国家自然科学基金海外青年学者合作研究基金(杰青B类),2008.1.1–2010.12.31.
段广仁 (PI),鲁棒控制理论及其在航天控制中的应用,教育部创新团队项目,2006.1.1–2009.12.31.
段广仁 (PI),鲁棒控制理论与应用,教育部长江学者特聘教授项目,2000.1.1–2004.12.31.
段广仁 (PI),控制系统设计的参数化方法及其应用,国家自然科学基金杰出青年科学基金项目,1999.1.1–2003.12.31.
科研平台
现有的科研平台如下,在此基础上,南方科技大学控制科学与工程学科的目标是争取获批一个省部级重点实验室和一个国家级重点实验室。
国家自然科学基金基础科学中心:高阶全驱系统理论与航天器控制技术
中心主任:段广仁
依托国家自然科学基金委基础科学中心这一国家级平台,解决颠覆性控制理论创新及航天器控制等应用方面的“卡脖子”问题,已成为控制领域全国顶尖的高端特色智库。
南方科技大学先进航空航天技术平台
学术带头人:甘晓华、段广仁
紧扣大力发展航空航天先进技术的重大国家战略,以航空燃气涡轮发动机、高阶全驱系统理论与航天器控制关键技术为战略研究方向,建设先进航空燃气涡轮发动机技术平台和先进航天器控制技术平台。
控制理论与智能系统深圳市重点实验室
实验室主任:段广仁
建设中.
机器人视觉与导航深圳市重点实验室
实验室主任:张宏
建设中.
机器人感知与智能深圳市重点实验室
实验室主任:孟庆虎
建设中.
全驱系统理论与应用
全驱系统理论的提出 见文档《全驱系统理论与应用.pdf》 研究进展