职称：副教授
所属部门：自动化系
办公室：机电信息实验大楼A232
联系方式：gdongsh@hqu.edu.cn,gdongsh2008@126.com
科研简介：
主要从事机器人控制、神经网络、数值算法、极限学习机器等研究工作。
项目情况：
1、国家自然科学基金青年项目，61603143，冗余度机械臂加速度层避障规划设计与分析，2017.01-2019.12，21万元，在研，主持
2、福建省自然科学基金面上项目，2016J01307，冗余度机械臂加速度规划的新技术及理论分析，2016.04-2019.04，5万元，在研，主持
3、永利平台中青年教师科技创新资助计划项目，ZQN-YX402，求解时变问题新方法的设计、开发及应用研究，2016.10-2020.09，80万元，在研，主持
4、2016年大员工创新创业训练计划项目，国家级，时变非线性优化问题求解的新算法及应用研究，1万元，在研，指导教师
小组成员：
*研究生：徐风(2016- .)
*本科生：林鑫杰、苏昭著、刘庆平、黄志静、孙思博、张志鑫(2016- .)
论文情况：
1.Dongsheng Guo, Zhuoyun Nie, and Laicheng Yan, “Novel discrete-time Zhang neural network for time-varying matrix inversion”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, in press, 2017.
2.Dongsheng Guo, Xinjie Lin, Zhaozhu Su, Sibo Sun, and Zhijing Huang, “Design and analysis of two discrete-time ZD algorithms for time-varying nonlinear minimization”, Numerical Algorithms, in press, 2017.
3.Dongsheng Guo, Zhuoyun Nie, and Laicheng Yan, “Theoretical analysis, numerical verification and geometrical representation of new three-step DTZD algorithm for time-varying nonlinear equations solving”, vol. 214, pp. 516-526, 2016.
4.Dongsheng Guoand Yunong Zhang, “ZNN for solving online time-varying linear matrix-vector inequality via equality conversion”, Applied Mathematics and Computation, vol. 259, pp. 327-338, 2015.
5.Dongsheng Guo, Yunong Zhang, Zhengli Xiao, Mingzhi Mao, and Jianxi Liu, “Common nature of learning between BP-type and Hopfield-type neural networks”, Neurocomputing, vol. 167, pp. 578-586, 2015.
6.Dongsheng Guoand Yunong Zhang, “Acceleration-level inequality-based MAN scheme for obstacle avoidance of redundant robot manipulators”, IEEE Transactions on Industrial Electronics, vol. 61, no. 12, pp. 6903-6914, 2014.
7.Dongsheng Guoand Yunong Zhang, “Zhang neural network for online solution of time-varying linear matrix inequality aided with an equality conversion”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 2, pp. 370-382, 2014.
8.Dongsheng Guoand Yunong Zhang, “Simulation and experimental verification of weighted velocity and acceleration minimization for robotic redundancy resolution”, IEEE Transactions on Automation Science and Engineering, vol. 11, no. 4, pp. 1203-1217, 2014.
