A study on effects of market systems in an artificial market

In an artificial market approach with multi-agent systems, the static equilibrium concept is often used in market systems to approximate continuous market auctions. However, differences between the static equilibrium concept and continuous auctions have not been discussed in the context of an artificial market study. In this paper, we construct an artificial market model with both of them, namely, the Itayose and Zaraba method, and show simple characteristic differences between these methods based on computer simulations. The result indicates the further need to model the market system by studying artificial markets. Hidenori Kawamura, Ph.D.: He received Ph.D. degree from Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University, Japan in 2000. He is currently an instructor in Graduate School of Information Science and Technology, Hokkaido University, Japan. His research interests include multiagent systems, mass user support, artificial intelligence, complex systems, and tourism informatics. He is a member of IPSJ, JSAI, IEICE, ORSJ, JSTI and AAAI. Yasushi Okada, Ph.D.: He is a master course student in Graduate School of Engineering, Hokkaido University, Japan. He studies multiagent systems. Azuma Ohuchi, Ph.D.: He received his Ph.D. degree in 1974 from Hokkaido University. He is currently the professor in Graduate School of Information Science and Technology, Hokkaido University Japan. His research interstes include systems information engineering, artificial intelligence, complex systems, tourism informatics and medical systems. He is a member of the IPSJ, JSAI, IEEJ, ORSJ, Soc. Contr. Eng., Jap. OR Soc., Soc. Med. Informatics, Hosp. Manag., JSTI and IEEE-SMC. Koichi Kurumatani, Ph.D.: He received his Ph.D. Degree in 1989 from The University of Tokyo. He is currently a leader of Multiagent Research Team in Cyber Assist Research Center (CARC), National Institute of Advanced Industrial Science and Technology (AIST), Japan. His research interests include multiagent systems and mass user support. He is a member of JSAI, IPSJ, JSTI and AAAI.     

Oscillation amplitude-controlled resonant accelerometer design using a reference tracking automatic gain control

In this paper, it is presented a novel approach for the self-sustained resonant accelerometer design, which takes advantages of an automatic gain control in achieving stabilized oscillation dynamics. Through the proposed system modeling and loop transformation, the feedback controller is designed to maintain uniform oscillation amplitude under dynamic input accelerations. The fabrication process for the mechanical structure is illustrated in brief. Computer simulation and experimental results show the feasibility of the proposed accelerometer design, which is applicable to a control grade inertial sense system. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Hyun Seok Yang. This work was supported by the BK21 Project ST·IT Fusion Engineering program in Konkuk University, 2008. This work was supported by the Korea Foundation for International Cooperation of Science & Technology(KICOS) through a grant provided by the Korean Ministry of Education, Science & Technology(MEST) in 2008 (No. K20601000001). Authors also thank to Dr. B.-L. Lee for the help in structure manufacturing. Sangkyung Sung is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the M.S and Ph.D. degrees in Electrical Engineering from Seoul National University in 1998 and 2003, respectively. His research interests include inertial sensors, avionic system hardware, navigation filter, and intelligent vehicle systems. Chang-Joo Kim is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aeronautical Engineering from Seoul National University in 1991. His research interests include nonlinear optimal control, helicopter flight mechanics, and helicopter system design. Young Jae Lee is a Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS related engineering problems. Jungkeun Park is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University. Dr. Park received the Ph.D. in Electrical Engineering and Computer Science from the Seoul National University in 2004. His current research interests include embedded real-time systems design, real-time operating systems, distributed embedded real-time systems and multimedia systems. Joon Goo Park is an Assistant Professor of the Department of Electronic Engineering at Gyung Book National University, Korea. He received the Ph.D. degree in School of Electrical Engineering from Seoul National University in 2001. His research interests include mobile navigation and adaptive control.     

Two fusion predictors for discrete-time linear systems with different types of observations

New fusion predictors for linear dynamic systems with different types of observations are proposed. The fusion predictors are formed by summation of the local Kalman filters/predictors with matrix weights depending only on time instants. The relationship between fusion predictors is established. Then, the accuracy and computational efficiency of the fusion predictors are demonstrated on the first-order Markov process and the GMTI model with multisensor environment. Recommended by Editorial Board member Lucy Y. Pao under the direction of Editor Young Il Lee. This work was partially supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korean government (MOST), No. R01-2007-000-20227-0 and the Center for Distributed Sensor Network at GIST. Ha-Ryong Song received the B.S. degree in Control and Instrumentation Engineering from the Chosun University, Korea, in 2006, the M.S. degree in School of Information and Mechatronics from the Gwangju Institute of Science and Technology, Korea, in 2007. He is currently a Ph.D. candidate in Gwangju Institute of Science and Technology. His research interests include estimation, target tracking systems, data fusion, nonlinear filtering. Moon-Gu Jeon received the B.S. degree in architectural engineering from the Korea University, Korea in 1988. He then received both the M.S. and Ph.D. degrees in computer science and scientific computation from the University of Minnesota in 1999 and 2001, respectively. Currently, he is an Associate Professor at the School of Information and Mechatronics of the Gwangju Institute of Science and Technology (GIST). His current research interests are in machine learning and pattern recognition and evolutionary computation. Tae-Sun Choi received the B.S. degree in Electrical Engineering from the Seoul National University, Seoul, Korea, in 1976, the M.S. degree in Electrical Engineering from the Korea Advanced Institute of Science and Technology, Seoul, Korea, in 1979, and the Ph.D. degree in Electrical Engineering from the State University of New York at Stony Brook, in 1993. He is currently a Professor in the School of Information and Mechatronics at Gwangju Institute of Science and Technology, Korea. His research interests include image processing, machine/robot vision, and visual communications. Vladimir Shin received the B.Sc. and M.Sc. degrees in Applied Mathematics from Moscow State Aviation Institute, in 1977 and 1979, respectively. In 1985 he received the Ph.D. degree in Mathematics at the Institute of Control Science, Russian Academy of Sciences, Moscow. He is currently an Associate Professor at Gwangju Institute of Science and Technology, South Korea. His research interests include estimation, filtering, tracking, data fusion, stochastic control, identification, and other multidimensional data processing methods.     

A grid-oriented genetic algorithm framework for bioinformatics

In this paper, we propose a framework for enabling for researchers of genetic algorithms (GAs) to easily develop GAs running on the Grid, named “Grid-Oriented Genetic algorithms (GOGAs)”, and actually “Gridify” a GA for estimating genetic networks, which is being developed by our group, in order to examine the usability of the proposed GOGA framework. We also evaluate the scalability of the “Gridified” GA by applying it to a five-gene genetic network estimation problem on a grid testbed constructed in our laboratory. Hiroaki Imade: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2001. He received the M.S. degree in information systems from the Graduate School of Engineering, The University of Tokushima in 2003. He is now in Doctoral Course of Graduate School of Engineering, The University of Tokushima. His research interests include evolutionary computation. He currently researches a framework to easily develop the GOGA models which efficiently work on the grid. Ryohei Morishita: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2002. He is now in Master Course of Graduate School of Engineering, The University of Tokushima, Tokushima. His research interest is evolutionary computation. He currently researches GA for estimating genetic networks. Isao Ono, Ph.D.: He received his B.S. degree from the Department of Control Engineering, Tokyo Institute of Technology, Tokyo, Japan, in 1994. He received Ph.D. of Engineering at Tokyo Institute of Technology, Yokohama, in 1997. He worked as a Research Fellow from 1997 to 1998 at Tokyo Institute of Technology, and at University of Tokushima, Tokushima, Japan, in 1998. He worked as a Lecturer from 1998 to 2001 at University of Tokushima. He is now Associate Professor at University of Tokushima. His research interests include evolutionary computation, scheduling, function optimization, optical design and bioinformatics. He is a member of JSAI, SCI, IPSJ and OSJ. Norihiko Ono, Ph.D.: He received his B.S. M.S. and Ph.D. of Engineering in 1979, 1981 and 1986, respectively, from Tokyo Institute of Technology. From 1986 to 1989, he was Research Associate at Faculty of Engineering, Hiroshima University. From 1989 to 1997, he was an associate professor at Faculty of Engineering, University of Tokushima. He was promoted to Professor in the Department of Information Science and Intelligent Systems in 1997. His current research interests include learning in multi-agent systems, autonomous agents, reinforcement learning and evolutionary algorithms. Masahiro Okamoto, Ph.D.: He is currently Professor of Graduate School of Systems Life Sciences, Kyushu University, Japan. He received his Ph.D. degree in Biochemistry from Kyushu University in 1981. His major research field is nonlinear numerical optimization and systems biology. His current research interests cover system identification of nonlinear complex systems by using evolutional computer algorithm of optimization, development of integrated simulator for analyzing nonlinear dynamics and design of fault-tolerant routing network by mimicking metabolic control system. He has more than 90 peer reviewed publications.     

Delay-dependent robust H ∞ control for uncertain fuzzy Markovian jump systems

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.     

Observer-based direct adaptive fuzzy control of uncertain nonlinear systems and its applications

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.     

The multi-objective optimal control with X - Q adaptive controller

This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system becomes better than that of the original system. Then, an example of the radar servo system is designed with a large phase angle allowance multi-objective optimal design method. Finally, the performance based on computer simulation demonstrates that the multi-objective optimal system is superior to linear optimal systems.     

Biologically inspired control of quadruped walking robot

In this paper, we present a control method for a quadruped walking robot inspired from the locomotion of quadrupeds. A simple and useful framework for controlling a quadruped walking robot is presented, which is obtained by observing the stimulus-reaction mechanism, the gravity load receptor and the manner of generating repetitive motions from quadrupeds. In addition, we propose a new rhythmic pattern generator that can relieve the large computational burden on solving the kinematics. The proposed method is tested via a dynamic simulation and validated by implementation in a quadruped walking robot, called AiDIN-I (Artificial Digitigrade for Natural Environment I). Recommended by Editorial Board member Sangdeok Park under the direction of Editor Jae-Bok Song. This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD) (KRF-2005-D00031). Ig Mo Koo received the B.S. degree in Mechanical Engineering from Myongji University, Yongin, Korea, in 2003, the M.S. degree in Mechanical Engineering from the Sungkyunkwan University, Suwon, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include artificial muscle actuators, haptics, tactile display, biomimetics and quadruped walking robots systems. Tae Hun Kang received the B.S., M.S., and Ph.D. degrees in Mechanical Engineering from Sungkyunkwan University, Korea, in 2000, 2002, and 2006, respectively. His current research interests focus on biomimetics and quadruped walking robot. Gia Loc Vo received the B.S degree in Mechanical Engineering form Ha Noi University of Technology in Vietnam 2003, the M.S. degree Mechanical Engineering form Sungkyunkwan University, Suwon, Korea, in 2006, where he is currently working toward a Ph.D. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include legged locomotion, walking and climbing robot. Tran Duc Trong received the B.S degree in Mechatronics from HoChiMinh City University of Technology in Vietnam in 2005, where he is currently working toward a M.S. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include biological inspired control and adaptive control of quadruped walking robot. Young Kuk Song received the B.S. degree in Mechanical Engineering from Sungkyunkwan University, Suwon, Korea, in 2006, where he is currently working toward a M.S. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include biomimetics, hydraulic robotics system and quadruped walking robot. Hyouk Ryeol Choi received the B.S. degree from Seoul National University, Seoul, Korea, in 1984, the M.S. degree from the Korea Advanced Technology of Science and Technology (KAIST), Daejeon, Korea, in 1986, and the Ph.D. degree from the Pohang University of Science and Technology (POSTECH), Pohang, Korea, in 1994. Since 1995, he has been with Sungkyunkwan University, Suwon, Korea, where he is currently a Professor in the School of Mechanical Engineering. He was an Associate Engineer with LG Electronics Central Research Laboratory, Seoul, Korea, from 1986 to 1989. From 1993 to 1995, he was with Kyoto University, Kyoto, Japan, as a grantee of scholarship funds from the Japanese Educational Administry. He visited the Advanced Institute of Industrial Science Technology (AIST), Tsukuba, Japan, as a JSPS Fellow from 1999 to 2000. He is now an Associate Editor in IEEE Transactions on Robotics, Journal of Intelligent Service Robotics, International Journal of Control, Automation and Systems (IJCAS). His interests includes dexterous mechanisms, field application of robots, and artificial muscle actua tors.     

Singularity Analysis of Geometric Constraint Systems

Singularity analysis in an important subject of the geometric constraint satisfaction problem.In this paper,three kinds of singularities are described and corresponding identifcation methods are presented for both under0constrained systems and over-constrained systems,Another special but common singularity for under-constrained geometric systems,pseudo-singularity,is analyzed.Pseudo-singularity is caused by a variety of constraint mathching of under-constrained systems and can be removed by improving constraint distribution.To avoid pseudo-singularity and decide redundant constraints adaptively,a differentiaiton algorithm is proposed in the paper.Its corrctness and effciency have been validated through its practical applications in a 2D/3D geometric constraint solver CBA.     

A new approach to fuzzy modeling and control for nonlinear dynamic systems: Neuro-fuzzy dynamic characteristic modeling and adaptive control mechanism

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.     

An enhanced force and contact position sensor for micro-manipulations

In micro-manipulations, force sensing devices play an important role in the control and the assembly of micro-objects. To protect these micro-objects from damage, we must have the ability to detect the value of the minute amount of interactive force (about a few μN) upon contact between the tip and the object. To detect this micro-force, we need an optimized design of force sensor to increase the strain values at the positions we place sensing components. Stress concentration can effectively amplify the strain values measured by the force sensors. This paper investigates the effect that the notches have on increasing the strain values at the positions we attach the sensing elements. In addition, the optimal design with a flexible structure improves the sensitivity of the sensor. An algorithm that can calculate both contact force and contact position on the sensor tip is also mentioned. Besides, an optimal location of strain gauges will ensure the accuracy and stability of the measurement. Finally, analysis and experiment are done to verify the proposed idea. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Jae-Bok Song. This research was supported by the Ministry of Knowledge Economy and Korean Industrial Technology Foundation through the Human Resource Training Project for Strategic Technology. Tri Cong Phung received the B.S. degree in Mechanical Engineering from the HCM University of Technology, Vietnam in 2004 and the M.S. degree in Mechanical Engineering from Sungkyunkwan University in 2007. He is currently working toward a Ph.D. degree in Intelligent Robotics and Mechatronic System Laboratory (IRMS Lab), Mechanical Engineering from Sungkyunkwan University. His research interests include dexterous manipulation and touch sensors. Seung Hwa Ha received the B.S. degree in Korean University of Technology and Education, Korea in 2004. He received the M.S. degree in Mechanical Engineering from Sungkyunkwan University in 2008. He is currently working in Samsung Electronic Co. Ltd. His research interests are about strain gauge and high precision control. Yong Seok Ihn received the B.S. degree in School of Mechanical Engineering from the Sungkyunkwan University, Korea in 2006. He received the M.S. degree in Mechanical Engineering from the Sungkyunkwan University, in 2008. He is currently working toward a Ph. D. degree in the Computer Aided Modeling & Simulation Laboratory (CAMAS Lab), School of Mechanical Engineering at the Sungkyunkwan University in Korea. His research interests are precision mechatronics, dynamic system modeling, and control. Byung June Choi received the B.S. degree in School of Mechanical Engineering from the Sungkyunkwan University, Korea in 2002. He received the M.S. degree in Mechanical Engineer-ing from the Sungkyunkwan University, in 2005. He is currently working toward a Ph.D. degree in the Intelligent Robotics and Mechatronic System Laboratory (IRMS Lab), School of Mechanical Engineering at the Sungkyunkwan University in Korea. His research interests are mechanisms design, multi-robot system control, cooperation, path planning and task allocation algorithm. Sang Moo Lee was born in Seoul, Korea and educated in Seoul. He received the Ph.D. degree from the Seoul National University in Korea, in 1999. He is currently a Principal Researcher of Division for Applied Robot Technology at Korean Institute of Industrial Technology. His research interests include high-precision robot control, motion field network, and location system in outdoor environment for robots. Ja Choon Koo is an Associate Professor of School of Mechanical Engineering in Sungkyunkwan University in Korea. His major researches are in the field of design, analysis, and control of dynamics systems, especially micro precision mechatronic systems and energy transducers. He was an Advisory Engineer for IBM, San Jose, California, USA and a Staff Engineer for SISA, San Jose, CA, USA. He received the Ph.D. and M.S. degrees from the University of Texas at Austin and the B.S. from Hanyang University, Seoul, Korea. Hyouk Ryeol Choi received the B.S. degree from Seoul National University, Seoul, Korea, in 1984, the M.S. degree from Korea Advanced Institute of Science and Technology (KAIST), Daejon, Korea, in 1986, and the Ph.D. degree from Pohang University of Science and Technology (POSTECH), Pohang, Korea, in 1994, all in Mechanical Engineering. From 1986 to 1989, he was an Associate Engineer at LG Electronics Central Research Laboratory, Seoul. From 1993 to 1995, he was at Kyoto University, Kyoto, Japan, as a Grantee of scholarship from the Japanese Educational Ministry. From 2000 to 2001, he visited Advanced Institute of Industrial Science Technology (AIST), Tsukuba, Japan, as a Japan Society for the Promotion of Sciences (JSPS) Fellow. Since 1995, he has been with Sungkyunkwan University, Suwon, Korea, where he is currently a Professor in the School of Mechanical Engineering. He is an Associate Editor of the Journal of Intelligent Service Robotics and International Journal of Control, Automation and Systems (IJCAS), and IEEE Transactions on Robotics. His current research interests include dexterous mechanism, field application of robots, and artificial muscle actuators.     

Managing quality-of-control and requirement-of-bandwidth in networked control systems via fuzzy bandwidth scheduling

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.     

Adaptive filtering under minimum information divergence criterion

Traditional filtering theory is always based on optimization of the expected value of a suitably chosen function of error, such as the minimum mean-square error (MMSE) criterion, the minimum error entropy (MEE) criterion, and so on. None of those criteria could capture all the probabilistic information about the error distribution. In this work, we propose a novel approach to shape the probability density function (PDF) of the errors in adaptive filtering. As the PDF contains all the probabilistic information, the proposed approach can be used to obtain the desired variance or entropy, and is expected to be useful in the complex signal processing and learning systems. In our method, the information divergence between the actual errors and the desired errors is chosen as the cost function, which is estimated by kernel approach. Some important properties of the estimated divergence are presented. Also, for the finite impulse response (FIR) filter, a stochastic gradient algorithm is derived. Finally, simulation examples illustrate the effectiveness of this algorithm in adaptive system training. Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Jae Weon Choi. This work was supported in part by the National Natural Science Foundation of China under grants 50577037 and 60604010. Badong Chen received the B.S. and M.S. degrees in Control Theory and Engineering from Chongqing University, Chongqing, China, in 1997 and 2003, respectively, and the Ph.D. degree in Computer Science and Technology from Tsinghua University, Beijing China, in 2008. He is currently a Postdoctor of the Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, China. His research interests are in signal processing, adaptive control, and information theoretic aspects of control systems. Yu Zhu received the B.S. of Radio Electronics in 1983 at Beijing Normal University, and the M.S. of Computer Applications in 1993, and the Ph.D. of Mechanical Design and Theory in 2001 at China University of Mining & Technology. He is now a Professor of the Institute of Manufacturing Engineering of Department of Precision and Mechanology of Tsinghua University. His current research interests are parallel machanism and theory, two photon micro-fabrication, ultra-precision motion system and motion control. Jinchun Hu received the Ph.D. in Control Science and Engineering from Nanjing University of Science and Technology, Nanjing, China, in 1998. Since then, he has been a postdoctoral researcher in Nanjing University of Aeronautics and Astronautics in 1999 and Tsinghua University in 2002 respectively. His research interests are in flight control, aerial Robot and intelligent control. Dr. Hu is currently an Associate Professor of the Department of Computer Science and Technology of Tsinghua University, Beijing, China. Zengqi Sun received the B.S. degree from the Department of Automatic Control, Tsinghua University, Beijing, China, in 1966 and the Ph.D. degree in Control Engineering from the Chalmas University of Technology, Sweden, in 1981. He is currently a Professor of the Department of Computer Science and Technology, Tsinghua University, Beijing, China. He is the author or coauthor of more than 100 paper and eight books on control and robotics. His research interests include robotics, intelligent control, fuzzy system, neural networks, and evolutionary computation.     

LMI stability criterion with less variables for time-delay systems

Slack variables approach is an important technique for tackling the delay-dependent stability problem for systems with time-varying delay. In this paper, a new delay-dependent stability criterion is presented without introducing any slack variable. The technique is based on a simply integral inequality. The result is shown to be equivalent to some existing ones but includes the least number of variables. Thus, redundant selection and computation can be avoided so that the computational burden can be largely reduced. Numerical examples are given to illustrate the effectiveness of the proposed stability conditions. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors would like to thank the Associate Editor and the Reviewers for their very helpful comments and suggestions. This work was supported in part by the Funds for Creative Research Groups of China under Grant 60821063, by the State Key Program of National Natural Science of China under Grant 60534010, by the Funds of National Science of China under Grant 60674021, 60774013, 60774047, National 973 Program of China under Grant No. 2009CB320604, and by the Funds of Ph.D. program of MOE, China under Grant 20060145019 and the 111 Project B08015. Xun-Lin Zhu received the B.S. degree in Applied Mathematics from Information Engineering Institute, Zhengzhou, China, in 1986, the M.S. degree in basic mathematics from Zhengzhou University, Zhengzhou, China, in 1989, and the Ph.D. degree in Control Theory and Engineer-ing from Northeastern University, Shenyang, China, in 2008. Currently, he is an Associate Professor at Zhengzhou University of Light Industry, Zhengzhou, China. His research interests include neural networks and networked control systems. Guang-Hong Yang received the B.S. and M.S. degrees in Northeast University of Technology, China, in 1983 and 1986, respectively, and the Ph.D. degree in Control Engineering from Northeastern University, China (formerly, Northeast University of Technology), in 1994. He was a Lecturer/Associate Professor with Northeastern University from 1986 to 1995. He joined the Nanyang Technological University in 1996 as a Postdoctoral Fellow. From 2001 to 2005, he was a Research Scientist/Senior Research Scientist with the National University of Singapore. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His current research interests include fault-tolerant control, fault detection and isolation, non-fragile control systems design, and robust control. Dr. Yang is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS), and an Associate Editor of the Conference Editorial Board of the IEEE Control Systems Society. Tao Li was born in 1979. He is now pursuing a Ph.D. degree in Research Institute of Automation Southeast University, China. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Chong Lin received the B.Sci and M.Sci in Applied Mathematics from the Northeastern University, China, in 1989 and 1992, respectively, and the Ph.D in Electrical and Electronic Engineering from the Nanyang Technological University, Singapore, in 1999. He was a Research Associate with the University of Hong Kong in 1999. From 2000 to 2006, he was a Research Fellow with the National University of Singapore. He is currently a Profesor with the Institute of Complexity Science, Qingdao University, China. His current research interests are mainly in the area of systems analysis and control. Lei Guo was born in 1966. He received the Ph.D. degree in Control Engineering from Southeast University (SEU), PR China, in 1997. 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. He also holds a Visiting Professor position in the University of Manchester, UK and an invitation fellowship in Okayama University, Japan. His research interests include robust control, stochastic systems, fault detection, filter design, and nonlinear control with their applications.     

A novel control loop design and its application to the force balance of vibratory rate sensor

This paper investigates a new loop design approach of force balance control for the vibratory rate sensor application. The proposed force balance control design takes advantages of the modified automatic gain control configuration in controlling the system’s oscillating dynamics at the sense mode. The adapted automatic gain control scheme and force balance strategy, which maintains a constant oscillation magnitude in the sense mode, have several advantages. First it is possible to analyze a complicated nonlinear feedback system using a linear control theory, which resulted in straightforward prediction of closed loop performance. Moreover the control system to achieve the design goals can be implemented using a relatively simple feedback configuration. An application to the vibratory rate sensor using the proposed automatic gain control configuration witnessed that the force balance control can be validated in a practical design process. Experiments using an actual micromachined rate sensor verified the feasibility of the proposed control scheme with demonstration of enhanced performance. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Hyun Seok Yang. This work was supported by the BK21 Project, ST-IT Fusion Engineering program in Konkuk University, 2008. This work was supported by the KICOS through a grant provided by the Korean Ministry of Education, Science & Technology in 2008 (No. K20601000001). Sangkyung Sung is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the M.S. and Ph.D. degrees in Electrical Engineering from Seoul National University in 1998 and 2003, respectively. His research interests include inertial sensors, avionic system hardware, integrated navigation, and intelligent vehicle technologies. Sukchang Yun is a Ph.D. course student of the Department of Aerospace Information Engineering at Konkuk University, Korea. He received the M.S. degree in Aerospace Engineering from Konkuk University in 2009. His research interests include MEMS mechatronics and control, INS/GPS integration, and instrumentation. Woon-Tahk Sung is an Senior Engineer of the Communication Reserarch Center, Samsung Electronics Co. Ltd. He received the Ph.D. degree in School of Electrical Engineering from Seoul National University in 2007. His research interests include analog and digital control algorithm, MEMS piezo actuator, circuit design for microsystems using VCM. Chang Joo Kim is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aeronautical Engineering from Seoul National University in 1991. His research interests include nonlinear optimal control, helicopter flight mechanics, and helicopter system design. Young Jae Lee is a Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS related engineering problems.     

In-pipe robot based on selective drive mechanism

This paper presents an in-pipe robot, called MRINSPECT V (Multifunctional Robotic crawler for In-pipe inSPECTion V), which is under development for the inspection of pipelines with a nominal 8-inch inside diameter. To travel freely in every pipeline element, the robot adopts a differential driving mechanism that we have developed. Furthermore, by introducing clutches in transmitting driving power to the wheels, MRINSPECT V is able to select the suitable driving method according to the shape of the pipeline and save the energy to drive in pipelines. In this paper, the critical points in the design and construction of the proposed robot are described with the preliminary results that yield good mobility and increased efficiency. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Jae-Bok Song. This work was supported by the Postdoctoral Research Program of Sungkyunkwan University (2008). Se-gon Roh received the B.S., M.S., and Ph.D degrees in Mechatronics Engineering from Sungkyunkwan University, Korea, in 1997, 1999, and 2006 respectively, and is currently a Researcher of the School of Mechanical Engineering also at Sungkyunkwan University. His research interests include mechanism design, applications of mobile robots, and in-pipe robots. Do Wan Kim received the B.S. degree in Mechanical Engineering from Sungkyunkwan University, Korea, in 2007. He is currently working toward a M.S. degree in Mechanical Engineering also at Sungkyunkwan University. His research interests include field robotics, in-pipe robots, and autonomous mobile robots. Jung-Sub Lee received the B.S. degree in Mechanical Engineering in 2008 from Sungkyunkwan University, Suwon, Korea, where he is currently working toward a M.S. degree in mechatronics engineering. His research interests include robot mechanism design, automation, and in-pipe robot. Hyungpil Moon received the B.S. and M.S. degrees in Mechanical Engineering from POSTECH in 1996 and 1998 respectively, and Ph.D. degree in Mechanical Engineering from University of Michigan in 2005. He joined the faculty of School of Mechanical Engineering in Sungkyunkwan University as a Full-time Lecturer in 2008. He was a Post-doctoral fellow at Carnegie Mellon University, Robotics Institute until November 2007. His research interests include distributed manipulation, multiple robot navigation, SLAM, and biomimetic robotics. Hyouk Ryeol Choi received the B.S. degree from Seoul National University in 1984, the M.S. degree from Korea Advanced Technology of Science and Technology (KAIST) in 1986, and the Ph.D. degree from Pohang University of Science and Technology (POSTECH) in 1994, Korea. Since 1995, he has been with Sungkyunkwan University, where he is currently a Professor of the School of Mechanical Engineering. He worked as an Associate Engineer with LG Electronics Central Research Laboratory from 1986 to 1989. From 1993 to 1995, he was with Kyoto University as a grantee of a scholarship from the Japanese Educational Ministry. He visited Advanced Institute of Industrial Science Technology (AIST), Japan as the JSPS Fellow, from 1999 to 2000. He is now an Associate Editor of IEEE Transactions on Robotics, International Journal of Control, System, Automation(IJCAS), and International Journal of Intelligent Service Robots (JISR). His interests include dexterous mechanisms, field applications of robots, and artificial muscle actuator.     

Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties

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.     

LMI-based robust iterative learning controller design for discrete linear uncertain systems

This paper addresses the design problem of robust iterative learning controllers for a class of linear discrete-time systems with norm-bounded parameter uncertainties. An iterative learning algorithm with current cycle feedback is proposed to achieve both robust convergence and robust stability. The synthesis problem of the proposed iterative learmng control （ILC） system is reformulated as a γ-suboptimal H-infinity control problem via the linear fractional transformation （LFT）. A sufficient condition for the convergence of the ILC algorithm is presented in terms of linear matrix inequalities （LMIs）. Furthermore, the linear wansfer operators of the ILC algorithm with high convergence speed are obtained by using existing convex optimization techniques. The simulation results demonstrate the effectiveness of the proposed method.     

Stability of nonlinear hybrid dynamical systems with time delay via sum of squares decomposition

Considering an infinite number of eigenvalues for time delay systems, it is difficult to determine their stability. We have developed a new approach for the stability test of time delay nonlinear hybrid systems. Construction of Lyapunov functions for hybrid systems is generally a difficult task, but once these functions are found, stability’s analysis of the system is straight-forward. In this paper both delay-independent and delay-dependent stability tests are proposed, based on the construction of appropriate Lyapunov-Krasovskii functionals. The methodology is based on the sum of squares decomposition of multivariate polynomials and the algorithmic construction is achieved through the use of semidefinite programming. The reduction techniques provide numerical solution of large-scale instances; otherwise they will be computationally infeasible to solve. The introduced method can be used for hybrid systems with linear or nonlinear vector fields. Finally simulation results show the correctness and validity of the designed method. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors wish to express their thanks to Dr. A. Papachristodoulou and Dr. M. Peet for their helpful comments and suggestions. Mohammad Ali Badamchizadeh was born in Tabriz, Iran, in December 1975. He received the B.S. degree in Electrical Engineering from University of Tabriz in 1998 and the M.Sc. degree in Control Engineering from University of Tabriz in 2001. He received the Ph.D. degree in Control Engineering from University of Tabriz in 2007. He is now an Assistant Professor in the Faculty of Electrical and Computer Engineering at University of Tabriz. His research interests include Hybrid dynamical systems, Stability of systems, Time delay systems, Robot path planning. Sohrab Khanmohammadi received the B.S. degree in Industrial Engineering from Sharif University, Iran in 1977 and the M.Sc. degree in Automatic from University Paul Sabatie, France in 1980 and the Ph.D. degree in Automatic from National University, ENSAE, France in 1983. He is now a Professor of Electrical Engineering at University of Tabriz. His research interests are Fuzzy control, Artificial Intelligence applications in control and simulation on industrial systems and human behavior. Gasem Alizadeh was born in Tabriz, Iran in 1967. He received the B.S. degree in Electrical Engineering from Sharif University, Iran in 1990 and the M.Sc. degree from Khajeh Nasir Toosi University, Iran in 1993 and the Ph.D. degree in Electrical Engineering from Tarbiat Modarres University, Iran in 1998. From 1998, he is a Member of University of Tabriz in Iran. His research interests are robust and optimal control, guidance, navigation and adaptive control. Ali Aghagolzadeh was born in Babol, Iran. He received the B.S. degree in Electrical Engineering in 1985 from University of Tabriz, Tabriz, Iran, and the M.Sc. degree in Electrical Engineering in 1988 from the Illinois Institute of Technology, Chicago, IL. He also attended the School of Electrical Engineering at Purdue University in August 1998 where he was also employed as a part-time research assistant and received the Ph.D. degree in 1991. He is currently an Associate Professor of Electrical Engineering at University of Tabriz, Tabriz, Iran. His research interests include digital signal and image processing, image coding and communication, computer vision, and image analysis.     

BCL—3：Aigh Performance Basic Communication Protocol for Commodity Superserver DAWNING—3000

This paper introduces the design and implemetation of BCL-3,a high performance low-level communication software running on a cluster of SMPs(CLUMPS) called DAWNING-3000,BCL-3 provides flexible and sufficient functionality to fulfill the communication requirements of fundamental system software developed for DAWNING-3000 while guaranteeing security,scalability,and reliability,Important features of BCL-3 are presented in the paper,including special support for SMP and heterogeneous network environment,semiuser-level communication,reliable and ordered data transfer and scalable flow control,The performance evaluation of BCL-3 over Myrinet is also given.