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国家自然科学基金(60904030)

作品数:4 被引量:6H指数:1
相关作者:费树岷宋爱国许莉娟裔扬朱清更多>>
相关机构:扬州大学东南大学江苏中惠医疗科技股份有限公司更多>>
发文基金:国家自然科学基金江苏省高校自然科学研究项目江苏省自然科学基金更多>>
相关领域:自动化与计算机技术理学更多>>

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4 条 记 录,以下是 1-10
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一类严格反馈非线性切换系统的鲁棒自适应控制
针对一类严格反馈非线性切换系统,利用后推技术、积分型李雅普诺夫函数、神经网络的逼近能力以及驻留时间法,提出一种自适应神经网络控制方案,通过引入逼近误差补偿项,并利用Young’s不等式,改善控制系统的性能。与已有文献相比...
朱柏城张天平高志远
关键词:切换系统李雅普诺夫稳定性
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Fuzzy Adaptive Control of Delayed High Order Nonlinear Systems被引量:1
2012年
This paper deals with the problem of tracking control for a class of high order nonlinear systems with input delay. The unknown continuous functions of the system are estimated by fuzzy logic systems (FLS). A state conversion method is introduced to eliminate the delayed input item. By means of the backstepping algorithm, the property of semi-globally uniformly ultimately bounded (SGUUB) of the closed-loop system is achieved. The stability of the closed-loop system is proved according to Lyapunov second theorem on stability. The tracking error is proved to be bounded which ultimately converges to an adequately small compact set. Finally, a computer simulation example of high order nonlinear systems is presented, which illustrates the effectiveness of the control scheme.
Qing ZhuAi-Guo SongTian-Ping ZhangYue-Quan Yang
关键词:高阶非线性系统模糊自适应控制一致最终有界模糊逻辑系统定理证明
一类非线性时滞系统的自适应动态面控制(英文)被引量:1
2013年
本文对于一类含不确定输入时滞和干扰的非线性系统的跟踪控制问题提出了一种自适应动态面控制方案.利用动态面控制方法避免了传统的后推设计中存在的复杂度爆炸问题.分别构造了一个滤波器和一个虚拟观测器来产生辅助信号.采用神经网络来逼近未知的连续函数.跟踪误差被证明最终收敛到一个足够小的紧集.给出了一个数字仿真示例验证了理论结果.
朱清宋爱国费树岷杨月全盛朗
关键词:动态面控制输入时滞神经网络自适应控制
Decentralized Tracking Control for Non-Gaussian Large-scale Interconnected Distribution Systems
This paper studies a novel constrained decentralized shaping control problem for nonlinear large-scale interco...
AN YaoYI YangZHENG WeixingZHANG Tianping
随机时滞马尔可夫跳变非线性系统的鲁棒耗散控制被引量:1
2010年
研究了Ittype不确定随机时滞马尔可夫跳变非线性系统的鲁棒耗散控制问题.该系统包含了Markov跳变参数、时变参数不确定性以及未知非线性函数,这些因素在实际中经常遇到且容易导致系统性能变差甚至不稳定.基于Lyapunov-Krasovskii函数的方法设计无记忆状态反馈耗散控制器,使得闭环系统对于所有容许的不确定性鲁棒随机稳定且严格(Q,S,R)-耗散.利用线性矩阵不等式形式给出了不确定随机马尔可夫跳变系统鲁棒随机稳定及严格(Q,S,R)-耗散问题可解的充分条件以及控制器的设计方法.最后,通过一个数值仿真验证了该方法的有效性.研究结果推广了现存的对于随机时滞马尔可夫跳变系统的H∞控制和无源控制的结论.
许莉娟张天平裔扬
关键词:马尔可夫过程耗散控制
Multi-objective PID control for non-Gaussian stochastic distribution system based on two-step intelligent models被引量:3
2009年
A new method for controlling the shape of the conditional output probability density function (PDF) for general nonlinear dynamic stochastic systems is proposed based on B-spline neural network (NN) model and T-S fuzzy model. Applying NN approximation to the measured PDFs, we transform the concerned problem into the tracking of given weights. Meanwhile, the complex multi-delay T-S fuzzy model with exogenous disturbances, parametric uncertainties and state constraints is used to represent the nonlinear weight dynamics. Moreover, instead of the non-convex design algorithms and PI control, the improved convex linear matrix inequality (LMI) algorithms and the generalized PID controller are proposed such that the multiple control objectives including stability, robustness, tracking performance and state constraint can be guaranteed simultaneously. Simulations are performed to demonstrate the efficiency of the proposed approach.
YI YangZHANG TianPingGUO Lei
关键词:B样条神经网络非高斯
融合全局和局部图像信息的水平集医学图像分割方法
针对医学成像伴随着弱边缘和灰度分布不均匀的问题,提出一种改进的变分水平集图像分割方法。该方法通过融合全局和局部图像信息建立一个具有一定灵敏性的模型,该模型通过调节全局项和局部项的权重系数对灰度不均匀图像进行有效分割。实验...
盛朗朱清陈进居小平
关键词:医学图像分割全局信息局部信息变分水平集
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Iterative Learning Control Algorithms Based on Complex Stochastic Distribution Systems
In this paper,a new generalized iterative learning algorithm is first proposed based on complex non-Gaussion s...
YI Yang~(1,2),SUN Changyin~1,GUO Lei~3 1.Institute of Automation,Southeast University,Nanjing 210096,P.R.China 2.College of Information Engineering,Yangzhou University,Yangzhou 225009,P.R.China 3.Science and Technology on Aircraft Control Laboratory,Beihang University,Beijing 100083,P.R.China
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Novel Statistic Information Control Framework for Non-Gaussian Stochastic Systems With Dead-Zone Input
<正>In this paper,a novel statistic information control framework is studied for non-Gaussian stochastic system...
YI Yang~(1
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Multi-objective PID control for non-Gaussian stochastic distribution system based on two-step intelligent models
A new method for controlling the shape of the conditional output probability density function(PDF) for general...
Yl Yang~(1+),ZHANG TianPing~1 & GUO Lei~2 1 Department of Automation,College of Information Engineering,Yangzhou University,Yangzhou 225009,China
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