刘冬，副教授，硕士生导师，毕业于东北大学控制理论与控制工程专业。研究方向：数据驱动控制、无模型自适应控制，强化学习等。主持国家自然科学基金青年基金项目，中央高校基本科研业务费项目，校博士启动基金项目。目前已发表及接受学术论文8篇。其中，SCI检索论文6篇，EI检索论文2篇。

主要相关成果：

[1] Dong Liu,  Guang-Hong Yang. Prescribed performance model-free adaptive integral  sliding mode control for discrete-time nonlinear systems, IEEE Transactions on Neural Networks and Learning Systems. (Regular Paper) 30(7) (2019) 2222-2230. (IF: 11.683).

[2] Dong Liu, Guang-Hong Yang. Data-driven adaptive sliding mode control of nonlinear discrete-time systems with prescribed performance [J] IEEE Transactions on Systems, Man, and Cybernetics: Systems. (Regular Paper) 49(12) (2019) 2598-2604. (IF: 9.309).

[3] Dong Liu, Guang-Hong Yang. Event-based model-free adaptive control for discrete-time nonlinear processes [J], IET Control Theory & Applications. 11(15) (2017) 2531-2538. (IF: 3.526).

[4] Dong Liu, Guang-Hong Yang. Neural network-based event-triggered MFAC for nonlinear discrete-time processes [J], Neurocomputing 272 (2018) 356-364. (IF: 4.072).

[5] Dong Liu,  Guang-Hong Yang. Performance-based data-driven model-free adaptive  sliding mode control for a class of discrete-time nonlinear processes  [J], Journal of Process Control, 68 (2018) 186-194. (IF: 3.316).

[6] Dong Liu,  Guang-Hong Yang. Model-free adaptive control design for nonlinear  discrete-time processes with reinforcement learning techniques [J],  49(11) (2018) 2298-2308. International Journal of Systems Science, (IF: 2.469).