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国家自然科学基金(60825303)

作品数:3 被引量:18H指数:2
相关作者:金飞虎钟啸剑高会军郭琦更多>>
相关机构:哈尔滨工业大学黑龙江生物科技职业学院更多>>
发文基金:国家自然科学基金中国博士后科学基金国家重点基础研究发展计划更多>>
相关领域:自动化与计算机技术电气工程更多>>

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Controller Synthesis of Continuous-Time Piecewise Linear Systems Based on Piecewise Lyapunov Functions
This paper investigates the robust H static output feedback(SOF) controller design for a class of continuous- ...
QIU Jianbin~1,FENG Gang~2,GAO Huijun~1 1.Space Control and Inertial Technology Research Center,Harbin Institute of Technology,Harbin 150001,P.R.China 2.Department of Manufacturing Engineering and Engineering Management,City University of Hong Kong,Kowloon,Hong Kong
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State Feedback Control for Networked Systems with Mixed Delays Subject to Quantization and Dropout Compensation
This paper deals with the state feedback control problem for networked systems with discrete and infinite dist...
Peng Shi is with the Faculty of Advanced Technology,University of Glamorgan,Pontypridd,CF37 1DL,U.K.He is also with the School of Engineering and Science,Victoria University,Melbourne,Vic 8001,Australia.Rongni Yang and Huijun Gao are with with the Space Control and Inertial Technology Research Center,Harbin Institute of Technology,Harbin 150001,China.
关键词:QUANTIZATIONCOMPENSATOR
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自适应蚁群算法在空间机器人路径规划中的应用被引量:12
2010年
为了弥补传统路径规划方法缺乏足够鲁棒性的问题,采用自适应蚁群算法实现了空间机器人路径规划.针对传统蚁群算法在计算初期出现停滞的现象,修改了信息激素物质的更新方法.自适应蚁群算法根据学习次数和与最近障碍物的距离来调节信息激素物质.仿真结果表明,该算法在采用较少蚂蚁的情况下,与一般蚁群算法相比,能够快速找到理想路径.
金飞虎高会军钟啸剑
关键词:蚁群算法空间机器人路径规划
Nonsynchronized state estimation of uncertain discrete-time piecewise affine systems被引量:1
2010年
This paper investigates the problem of robust H-infinity state estimation for a class of uncertain discretetime piecewise affine systems where state space instead of measurable output space partitions are assumed so that the filter implementation may not be synchronized with plant state trajectory transitions. Based on a piecewise quadratic Lyapunov function combined with S-procedure and some matrix inequality convexifying techniques, two different approaches are developed to the robust filtering design for the underlying piecewise affine systems. It is shown that the filter gains can be obtained by solving a set of linear matrix inequalities (LMIs). Finally, a simulation example is provided to illustrate the effectiveness of the proposed approaches.
Jianbin QIUGang FENGHuijun GAO
基于蚁群算法的Hopfield神经网络在多空间站路径规划的应用研究被引量:5
2010年
空间机器人每次携带的燃料有限,提高空间机器人的工作效率以及延长其在轨寿命研究具有重要意义,分析了空间机器人多空间站访问问题。为了弥补传统路径规划方法容易陷入局部极小点的问题,提出利用基于蚁群算法的Hopfield神经网络来解决空间机器人多空间站访问问题。仿真实验结果表明,基于蚁群算法的Hopfiled神经网络用于多空间站访问问题,收敛速度要比Hopfield神经网络快,且比Hopfield神经网络易于跳出局部极点,该算法有利于解决多空间站路径规划问题。
金飞虎郭琦
关键词:蚁群算法空间机器人HOPFIELD神经网络
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