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1.
Yan-Jun Liu Shao-Cheng Tong Wei Wang Yong-Ming Li 《International Journal of Control, Automation and Systems》2009,7(4):681-690
A direct adaptive fuzzy control algorithm is developed for a class of uncertain SISO nonlinear systems. In this algorithm,
it doesn’t require to assume that the system states are measurable. Therefore, it is needed to design an observer to estimate
the system states. Compared with the numerous alternative approaches with respect to the observer design, the main advantage
of the developed algorithm is that on-line computation burden is alleviated. It is proven that the developed algorithm can
guarantee that all the signals in the closed-loop system are uniformly ultimately bounded and the tracking error converges
to a small neighborhood around zero. The simulation examples validate the feasibility of the developed algorithm.
Recommended by Editorial Board member Zhong Li under the direction of Editor Young-Hoon Joo. This work is supported by National
Natural Science Foundation of China under grant 60674056, 60874056, and the Foundation of Educational Department of Liaoning
Province (2008312).
Yan-Jun Liu received the B.S. degree in Applied Mathematics from Shenyang University of Technology in 2001. He received the M.S. degree
in Control Theory and Control Engineering from Shenyang University of Technology in 2004 and the Ph.D. degree in Control Theory
and Control Engineering from Dalian University of Technology, China, in 2007. His research interests include fuzzy control
theory, nonlinear control and adaptive control.
Shao-Cheng Tong received the B.S. degree in Department of Mathematics from Jinzhou Normal College, China, in 1982. He received the M.S. degree
in Department of Mathematics from Dalian Marine University in 1988 and the Ph.D. degree in Control Theory and Control Engineering
from Northeastern University, China, in 1997. His research interests include fuzzy control theory, nonlinear control, adaptive
control, and system identification etc.
Wei Wang received the B.S. degree in Department of Automation from Northeastern University, China, in 1982. He received the M. S.
degree in Department of Automation from Northeastern University in 1984 and the Ph.D. degree in Department of Automation from
Northeastern University, China, in 1988. His research interests include adaptive predictive control, intelligent control,
and production scheduling method etc.
Yong-Ming Li received the B.S. degree in Applied Mathematics from Liaoning University of Technology in 2004. He received the M.S. degree
in Applied Mathematics from Liaoning University of Technology in 2007. His research interests include fuzzy control theory,
nonlinear control and adaptive control. 相似文献
2.
Xiong Luo Zengqi Sun Fuchun Sun 《International Journal of Control, Automation and Systems》2009,7(1):123-132
The study on nonlinear control system has received great interest from the international research field of automatic engineering.
There are currently some alternative and complementary methods used to predict the behavior of nonlinear systems and design
nonlinear control systems. Among them, characteristic modeling (CM) and fuzzy dynamic modeling are two effective methods.
However, there are also some deficiencies in dealing with complex nonlinear system. In order to overcome the deficiencies,
a novel intelligent modeling method is proposed by combining fuzzy dynamic modeling and characteristic modeling methods. Meanwhile,
the proposed method also introduces the low-level learning power of neural network into the fuzzy logic system to implement
parameters identification. This novel method is called neuro-fuzzy dynamic characteristic modeling (NFDCM). The neuro-fuzzy
dynamic characteristic model based overall fuzzy control law is also discussed. Meanwhile the local adaptive controller is
designed through the golden section adaptive control law and feedforward control law. In addition, the stability condition
for the proposed closed-loop control system is briefly analyzed. The proposed approach has been shown to be effective via
an example.
Recommended by Editor Young-Hoon Joo. This work was jointly supported by National Natural Science Foundation of China under
Grant 60604010, 90716021, and 90405017 and Foundation of National Laboratory of Space Intelligent Control of China under Grant
SIC07010202.
Xiong Luo received the Ph.D. degree from Central South University, Changsha, China, in 2004. From 2005 to 2006, he was a Postdoctoral
Fellow in the Department of Computer Science and Technology at Tsinghua University. He currently works as an Associate Professor
in the Department of Computer Science and Technology, University of Science and Technology Beijing. His research interests
include intelligent control for spacecraft, intelligent optimization algorithms, and intelligent robot system.
Zengqi Sun received the bachelor degree from Tsinghua University, Beijing, China, in 1966, and the Ph.D. degree from Chalmers University
of the Technology, Gothenburg, Sweden, in 1981. He currently works as a Professor in the Department of Computer Science and
Technology, Tsinghua University. His research interests include intelligent control of robotics, fuzzy neural networks, and
intelligent flight control.
Fuchun Sun received the Ph.D. degree from Tsinghua University, Beijing, China, in 1998. From 1998 to 2000, he was a Postdoctoral Fellow
in the Department of Automation at Tsinghua University, where he is currently a Professor in the Department of Computer Science
and Technology. His research interests include neural-fuzzy systems, variable structure control, networked control systems,
and robotics. 相似文献
3.
Tao Li Lei Guo Lingyao Wu Changyin Sun 《International Journal of Control, Automation and Systems》2009,7(2):281-287
This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties
of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability
criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide
less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed
approach.
Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Young-Hoon Joo. This work was supported
by the National Science foundation of China under Grant no. 60774013 and Key Laboratory of Education Ministry for Image Processing
and Intelligent Control under grant no. 200805.
Tao Li received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor
in Department of Information and Communication, Nanjing University of Information Science and Technology. His current research
interests include time-delay systems, neural networks, robust control, fault detection and diagnosis.
Lei Guo received the Ph.D. degree in the Research Institute of Automation Southeast University, China. From 1999 to 2004, he has
worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now He is a Professor
in School of Instrument Science and Opto-Electronics Engineering, Beihang University. His current research interests include
robust control, fault detection and diagnosis.
Lingyao Wu received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor
in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural
networks, robust control, fault detection and diagnosis.
Changyin Sun received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a Professor in the
Research Institute of Automation Southeast University. His current research interests include timedelay systems, neural networks. 相似文献
4.
Zuxin Li Wanliang Wang Yunliang Jiang 《International Journal of Control, Automation and Systems》2009,7(2):289-296
There is an unavoidable tradeoff between the control performance and the quality of service in networked control systems with
resource constraints. To address the impact of network resources availability on requirement of bandwidth (RoB) and quality
of control (QoC), an intelligent control approach to dynamic bandwidth management, namely fuzzy bandwidth management, is proposed
based on fuzzy logic control technique. In order to guarantee the system’s stability, the lower and upper bound of the assignable
bandwidth are evaluated in terms of linear matrix inequalities and the resource constraints, respectively. In addition, the
normalizable criterions of QoC and RoB are also defined, which can estimate the performance of the whole networked control
systems. Preliminary simulations are carried out to highlight the merits of the proposed approach. It is argued that the proposed
approach can save significant bandwidth and simultaneously improve overall control performance in comparison with the fixed
bandwidth allocation and optimal bandwidth allocation.
Recommended by Editorial Board member Young Il Lee under the direction of Editor Young-Hoon Joo. This work was supported by
the National Natural Science Foundation of China under Grants 60573123, 60872057, and by the Zhejiang Provincial Natural Science
Foundation of China under grant Y107293.
Zuxin Li received the B.Eng. degree from Zhejiang University of Technology, China, in 1995, the M.Sc. (Eng.) degree from Yunnan Univer-sity,
China, in 2002, and the Ph.D. degree from Zhejiang University of Technology, China, in 2008. He is currently an Associate
Professor in the School of Information Engineering, Huzhou Teachers College, China. His research interests include networked
control systems and intelligent control.
Wanliang Wang received the Ph.D. degree from Tongji University, China, in 2001. He is currently a Professor in Zhejiang University of Technology,
China. His research interests include computer control, computer net, CMIS, and production scheduling.
Yunliang Jiang received the B.S. degree in Mathematics from Zhejiang Normal University in 1989, and the M.E. and Ph.D. degrees in Computer
Science and Technology from Zhejiang University, Hangzhou, China. He is currently a Professor in the School of Information
Engineering, Huzhou Teachers College, China. His research interests include information fusion, artificial intelligence, and
geographic information system. 相似文献
5.
New Meta-Heuristic for Combinatorial Optimization Problems: Intersection Based Scaling 总被引:1,自引:0,他引:1 下载免费PDF全文
PengZou ZhiZhou Ying-YuWan Guo-LiangChen JunGu 《计算机科学技术学报》2004,19(6):0-0
Combinatorial optimization problems are found in many application fields such as computer science,engineering and economy. In this paper, a new efficient meta-heuristic, Intersection-Based Scaling (IBS for abbreviation), is proposed and it can be applied to the combinatorial optimization problems. The main idea of IBS is to scale the size of the instance based on the intersection of some local optima, and to simplify the search space by extracting the intersection from the instance, which makes the search more efficient. The combination of IBS with some local search heuristics of different combinatorial optimization problems such as Traveling Salesman Problem (TSP) and Graph Partitioning Problem (GPP) is studied, and comparisons are made with some of the best heuristic algorithms and meta-heuristic algorithms. It is found that it has significantly improved the performance of existing local search heuristics and significantly outperforms the known best algorithms. 相似文献
6.
Bing Wang Haibo Ji Jin Zhu 《International Journal of Control, Automation and Systems》2009,7(1):41-48
This paper investigates the problem of global robust stabilization for a wide class of nonlinear systems, called polynomial
lower-triangular form (pLTF), which expands LTF to a more general case. The aim is explicitly constructing the smooth controller
for the class of systems with static uncertainties, by adding and modifying a power integrator in a recursive manner. The
pLTF relaxes the restrictions on the structure of the normal LTF and enlarges the family of systems that are stabilizable.
Examples are also provided to show the practical usage of this class of systems and the effectiveness of the design method.
Recommended by Editorial Board member Hyungbo Shim under the direction of Editor Jae Weon Choi.
Bing Wang received the B.S. degree from the Huazhong University of Science and Technology, and the Ph.D. degree from the University
of Science and Technology of China, in 1998 and 2006, respectively. He is currently working in College of Electrical Engineering,
Hohai University. His research interests include robust control, nonlinear control and power systems.
Haibo Ji received the B.S. and Ph.D. degrees in Mechanical Engineering from ZheJiang University and Beijing University in 1984 and
1990 respectively. He is currently a Professor in the Dept. of Automation, USTC. His research interests include nonlinear
control and adaptive control.
Jin Zhu received the B.S. and Ph.D. degrees in Control Science and Engineering from University of Science & Technology of Chinain
2001 and 2006 respectively. He is currently a Post-doc in Han-Yang University, Korea. His research interests include Markovian
jump systems and nonlinear control. 相似文献
7.
Yashun Zhang Shengyuan Xu Jihui Zhang 《International Journal of Control, Automation and Systems》2009,7(4):520-529
This paper is concerned with the problem of delay-dependent robust H
∞ control for uncertain fuzzy Markovian jump systems with time delays. The purpose is to design a mode-dependent state-feedback
fuzzy controller such that the closed-loop system is robustly stochastically stable and satisfies an H
∞ performance level. By introducing slack matrix variables, a delay-dependent sufficient condition for the solvability of the
problem is proposed in terms of linear matrix inequalities. An illustrative example is finally given to show the applicability
and effectiveness of the proposed method.
Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. This work is supported by
the National Science Foundation for Distinguished Young Scholars of P. R. China under Grant 60625303, the Specialized Research
Fund for the Doctoral Program of Higher Education under Grant 20060288021, and the Natural Science Foundation of Jiangsu Province
under Grant BK2008047.
Yashun Zhang received the B.S. and M.S. degrees in Control Science and Control Engineering from Hefei University of Science and Technology
in 2003 and 2006. He is currently a Ph.D. student in Control Science and Control Engineering, Nanjing University of Science
and Technology. His research interests include fuzzy control, sliding mode control and nonlinear control.
Shengyuan Xu received the Ph.D. degree in Control Science and Control Engineering from Nanjing University of Science and Technology in
1999. His research interests include robust filtering and control, singular systems, time-delay systems and nonlinear systems.
Jihui Zhang is a Professor in the School of Automation Engineering of Qingdao University, China. His main areas of interest are discrete
event dynamic systems, production planning and control, and operations research. 相似文献
8.
Survey on the stability of networked control systems 总被引:1,自引:0,他引:1
The insertion of the communication network in the feedback control loop makes the analysis and design of a network control system more complex, and induces some issues that degrade the control system’s performance and even cause system instability. The main aspects are focused on the stability analysis of Network Control Systems (NCSs) with network-induced delays, data packet dropouts, and multiple-packet transmission. These issues must be considered in the design of an NCS. This work summarizes the main research results, and remarks on some related handling approaches and techniques. The main purpose of the survey is to present the new research state of NCSs and to point out some fields of future work. 相似文献
9.
A General Probability Formula of the Number of Location Areas' Boundaries Crossed by a Mobile Between Two Successive Call Arrivals 总被引:1,自引:0,他引:1 下载免费PDF全文
Yi-HuaZhu Ding-HuaShi YongXiong JiGao He-ZhiLuo 《计算机科学技术学报》2004,19(2):177-182
Mobility management is a challenging topic in mobile computing environment. Studying the situation of mobiles crossing the boundaries of location areas is significant for evaluating the costs and performances of various location management strategies. Hitherto, several formulae were derived to describe the probability of the number of location areas‘ boundaries crossed by a mobile. Some of them were widely used in analyzing the costs and performances of mobility management strategies. Utilizing the density evolution method of vector Markov processes, we propose a general probability formula of the number of location areas‘ boundaries crossed by a mobile between two successive calls. Fortunately, several widely-used formulae are special cases of the proposed formula. 相似文献
10.
Yugang Niu Bei Chen Xingyu Wang 《International Journal of Control, Automation and Systems》2009,7(3):365-370
This paper deals with the problem of sliding mode control (SMC) for a class of nonlinear stochastic systems. The nonlinear
uncertainties are unknown and unmatched. There exist state and input delays. A special switching function is designed such
that the insensitivity of the system can be guaranteed throughout the entire response of the system from the initial time
instance. Both the sliding surface and the sliding mode controller exist if a set of matrix inequalities is feasible. A simulation
example is given to illustrate the proposed method.
Recommended by Editorial Board member Poo Gyeon Park under the direction of Editor Young Il lee. The research was partially
supported by NNSF under Grant (60674015, 60674089), the Technology Innovation Key Foundation of Shanghai Municipal Education
Commission (09ZZ60), Shanghai Leading Academic Discipline Project (B504), China.
Yugang Niu received the Ph.D. degree in Control Theory and Control Engineering Automation from Nanjing University of Science and Technology
in 2001. His research interests include nonlinear control, stochastic control systems, sliding mode control and network congestion
control.
Bei Chen received the B.S. degree in Automation from East China University of Science & Technology in 2008. Her current research areas
are sliding mode control, and networked control systems.
Xingyu Wang received the Ph.D. degree in Industrial Automation from the East China Chemical Institute in 1984. His current research areas
primarily cover control theory and applications, intelligent control, and brain control with its wide range of applications. 相似文献