吴淮宁
鲁棒控制与滤波、容错控制、模糊/神经建模与控制、时滞系统,Markovian跳变系统以及分布参数系统等。
个性化签名
- 姓名:吴淮宁
- 目前身份:
- 担任导师情况:
- 学位:
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学术头衔:
教育部“新世纪优秀人才支持计划”入选者, 博士生导师
- 职称:-
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学科领域:
控制理论
- 研究兴趣:鲁棒控制与滤波、容错控制、模糊/神经建模与控制、时滞系统,Markovian跳变系统以及分布参数系统等。
吴淮宁,教授,博导。1972年11月15日生于安徽省枞阳县。1988.9-1992.7于山东建材学院自动化系生产过程自动化专业学习,获学士学位。1992.9-1997.6于西安交通大学信息与控制工程系现代控制理论与应用专业学习,获博士学位。2000年7月晋升为副教授,2008年6月被增列为控制理论与控制工程专业博士生导师,2008年7月晋升为教授。
工作经历:
1997.8-1999.7于北京理工大学电子工程系从事博士后研究;
1999.8-今于北京航空航天大学任教;
2005.12-2006.5于香港城市大学任Senior Research Associate;
2006.10-2006.12、2007.10-2007.12、2008.10-2008.12、2010.7-2010.8于香港城市大学任Research Fellow。
研究领域与学科方向:
研究领域:鲁棒控制与滤波、容错控制、模糊/神经建模与控制、时滞系统,Markovian跳变系统以及分布参数系统等。
学科方向:控制理论与控制工程。
主授课程:
研究生课程《鲁棒控制》
留学生课程《Robust Control》
本科生课程《智能控制导论》
学术荣誉:
2007年,荣获教育部自然科学奖一等奖,排名第5。
2006年,入选教育部“新世纪优秀人才支持计划”。
2005年,入选北京航空航天大学《蓝天计划》“蓝天(科研)新星” 。
学术兼职:
现任中国自动化学会技术过程故障诊断与安全性专业委员会委员。
国内外多家著名学术刊物审稿人,主要包括
IEEE Transactions on Automatic Control
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics
IEEE Transactions on Aerospace and Electronic Systems
IET Control Theory & Applications
Automatica
International Journal of Approximate Reasoning
Fuzzy Sets and Systems
Information Sciences
自动化学报、控制理论与应用等。
代表论著和成果:
在IEEE Trans. Neural Netw.、IEEE Trans. Fuzzy Syst.、IEEE Trans. Syst. Man Cybern. Part B-Cybern.、IEEE Trans. Circuits Syst. II-Express Briefs、Automatica、Int. J. Robust Nonlinear Control、J. Dyn. Syst. Meas. Control-Trans. ASME、Fuzzy Sets Syst.、Int. J. Approx. Reasoning、Information Sciences、《自动化学报》、《控制理论与应用》等国内外重要学术刊物以及会议上发表论文50余篇,其中SCI源期刊论文27篇。
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1361
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成果阅读
198
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成果数
5
【期刊论文】H∞ fuzzy control design of discrete-time nonlinear active fault-tolerant control systems
吴淮宁, Huai-Ning Wu?, ?
Int. J. Robust Nonlinear Control 2009; 19: 1129-1149,-0001,():
-1年11月30日
This paper is concerned with the problem of H∞ fuzzy controller synthesis for a class of discrete-time nonlinear active fault-tolerant control systems (AFTCSs) in a stochastic setting. The Takagi and Sugeno (T-S) fuzzy model is employed to exactly represent a nonlinear AFTCS. For this AFTCS, two random processes with Markovian transition characteristics are introduced to model the failure process of system components and the fault detection and isolation (FDI) decision process used to reconfigure the control law, respectively. The random behavior of the FDI process is conditioned on the state of the failure process. A non-parallel distributed compensation (non-PDC) scheme is adopted for the design of the fault-tolerant control laws. The resulting closed-loop fuzzy system is the one with two Markovian jump parameters. Based on a stochastic fuzzy Lyapunov function (FLF), sufficient conditions for the stochastic stability and H∞ disturbance attenuation of the closed-loop fuzzy system are first derived. A linear matrix inequality (LMI) approach to the fuzzy control design is then developed. Moreover, a suboptimal fault-tolerant H∞ fuzzy controller is given in the sense of minimizing the level of disturbance attenuation. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.
fault-tolerant control, fuzzy control, H∞ control, linear matrix inequality (, LMI), , nonlinear systems, stochastic stability
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吴淮宁
,-0001,():
-1年11月30日
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30浏览
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吴淮宁, Huai-Ning Wu
International Journal of Approximate Reasoning 46(2007)151-165,-0001,():
-1年11月30日
This paper deals with the robust H2 fuzzy observer-based control problem for discrete-time uncertain nonlinear systems. The Takagi and Sugeno (T–S) fuzzy model is employed to represent a discrete-time nonlinear system with parametric uncertainties. A fuzzy observer is used to estimate the state of the fuzzy system and a non-parallel distributed compensation (non-PDC) scheme is adopted for the control design. A fuzzy Lyapunov function (FLF) is constructed to derive a sufficient condition such that the closed-loop fuzzy system is globally asymptotically stable and an upper bound on the quadratic cost function is provided. A sufficient condition for the existence of a robust H2 fuzzy observer-based controller is presented in terms of linear matrix inequalities (LMIs). Moreover, by using the existing LMI optimization techniques, a suboptimal fuzzy observer-based controller in the sense of minimizing the cost bound is proposed. Finally, an example is given to illustrate the effectiveness of the proposed design method.
Discrete-time nonlinear systems, Fuzzy control, H2 control, Linear matrix inequality (, LMI), , Parametric uncertainty, State observer
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吴淮宁, Huai-Ning Wu *, Kai-Yuan Cai
Information Sciences 177(2007)1509-1522,-0001,():
-1年11月30日
This paper studies the robust fuzzy control problem of uncertain discrete-time nonlinear Markovian jump systems without mode observations. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a discrete-time nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. As a result, an uncertain Markovian jump fuzzy system (MJFS) is obtained. A stochastic fuzzy Lyapunov function (FLF) is employed to analyze the robust stability of the uncertain MJFS, which not only is dependent on the operation modes of the system, but also directly includes the membership functions. Then, based on this stochastic FLF and a non-parallel distributed compensation (non-PDC) scheme, a mode-independent state-feedback control design is developed to guarantee that the closed-loop MJFS is stochastically stable for all admissible parameter uncertainties. The proposed sufficient conditions for the robust stability and mode-independent robust stabilization are formulated as a set of coupled linear matrix inequalities (LMIs), which can be solved efficiently by using existing LMI optimization techniques. Finally, it is also demonstrated, via a simulation example, that the proposed design method is effective.
Uncertain nonlinear systems, Markovian jump parameters, Robust control, Fuzzy control, Linear matrix inequality (, LMI), , Stochastic stability
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吴淮宁, Huai-NingWu?, Kai-Yuan Cai
Automatica 42(2006)1183-1188,-0001,():
-1年11月30日
This paper presents a design method of H2 guaranteed cost (GC) fuzzy controllers for discrete-time nonlinear systems with parameter uncertainties. The Takagi and Sugeno (T-S) fuzzy model with parameter uncertainties is employed to represent an uncertain discrete-time nonlinear system. A sufficient condition for the existence of H2 GC fuzzy controllers is presented in terms of linear matrix inequalities (LMIs). The resulting fuzzy controllers not only guarantee that the closed-loop fuzzy system is quadratically stable, but also provide a guaranteed cost on the H2 performance index. Furthermore, an optimal H2 GC fuzzy controller in the sense of minimizing a bound on the guaranteed cost is provided by means of an LMI optimization procedure. Finally, it is also demonstrated, through numerical simulations on the backing up control of a truck-trailer, that the proposed design method is effective.
Discrete-time nonlinear systems, Fuzzy control, Linear matrix inequality (, LMI), , Takagi and Sugeno fuzzy model
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