Object-spatial layout-route based hybrid map and global localization for mobile robots

This paper presents new object-spatial layout-route based hybrid map representation and global localization approaches using a stereo camera. By representing objects as high-level features in a map, a robot can deal more effectively with different contexts such as dynamic environments, human-robot interaction, and semantic information. However, the use of objects alone for map representation has inherent problems. For example, it is difficult to represent empty spaces for robot navigation, and objects are limited to readily recognizable things. One way to overcome these problems is to develop a hybrid map that includes objects and the spatial layout of a local space. The map developed in this research has a hybrid structure that combines a global topological map and a local hybrid map. The topological map represents the spatial relationships between local spaces. The local hybrid map combines the spatial layout of the local space with the objects found in that space. Based on the proposed map, we suggest a novel coarse-to-fine global localization method that uses object recognition, point cloud fitting and probabilistic scan matching. This approach can accurately estimate robot pose with respect to the correct local space. Recommended by Editor Jae-Bok Song. This research was performed for the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea. Soonyong Park received the B.S. and M.S. degrees from the Department of Mechanical Engineering, Kyunghee University, Seoul, Korea, in 2001 and 2003, respectively. He is currently working toward the Ph.D. degree in the Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea. Since 2001, he has been a student researcher in the Center for Cognitive Robotics Research, Korea Institute of Science and Technology (KIST), Seoul, Korea. His research interests include mobile robot navigation and computer vision. Mignon Park received the B.S. and M.S. degrees in Electronics from Yonsei University, Seoul, Korea, in 1973 and 1977, respectively. He received the Ph.D. degree in University of Tokyo, Japan, 1982. He was a researcher with the Institute of Biomedical Engineering, University of Tokyo, Japan, from 1972 to 1982, as well as at the Massachusetts Institute of Technology, Cambridge, and the University of California Berkeley, in 1982. He was a visiting researcher in Robotics Division, Mechanical Engineering Laboratory, Ministry of International Trade and Industry, Tsukuba, Japan, from 1986 to 1987. He has been a Professor in the Department of Electrical and Electronic Engineering in Yonsei University, since 1982. His research interests include fuzzy control and application, robotics, and fuzzy biomedical system. Sung-Kee Park is a principal research scientist for Korea Institute of Science and Technology (KIST). He received the B.S. and M.S. degrees in Mechanical Design and Production Engineering from Seoul National University, Seoul, Korea, in 1987 and 1989, respectively. He received the Ph.D. degree (2000) from Korea Advanced Institue of Science and Technology (KAIST), Korea, in the area of computer vision. Since then, he has been working for the center for cognitive robotics research at KIST. During his period at KIST, he held a visiting position at the Robotics Institute of Carnegie Mellon University in 2005, where he did research on object recognition. His recent work has been on cognitive visual processing, object recognition, visual navigation, and human-robot interaction.     

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.     

Mobile robot localization based on effective combination of vision and range sensors

Most localization algorithms are either range-based or vision-based, but the use of only one type of sensor cannot often ensure successful localization. This paper proposes a particle filter-based localization method that combines the range information obtained from a low-cost IR scanner with the SIFT-based visual information obtained from a monocular camera to robustly estimate the robot pose. The rough estimation of the robot pose by the range sensor can be compensated by the visual information given by the camera and the slow visual object recognition can be overcome by the frequent updates of the range information. Although the bandwidths of the two sensors are different, they can be synchronized by using the encoder information of the mobile robot. Therefore, all data from both sensors are used to estimate the robot pose without time delay and the samples used for estimating the robot pose converge faster than those from either range-based or vision-based localization. This paper also suggests a method for evaluating the state of localization based on the normalized probability of a vision sensor model. Various experiments show that the proposed algorithm can reliably estimate the robot pose in various indoor environments and can recover the robot pose upon incorrect localization. Recommended by Editorial Board member Sooyong Lee under the direction of Editor Hyun Seok Yang. This research was conducted by the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea. Yong-Ju Lee received the B.S. degree in Mechanical Engineering from Korea University in 2004. He is now a Student for Ph.D. of Mechanical Engineering from Korea University. His research interests include mobile robotics. Byung-Doo Yim received the B.S. degree in Control and Instrumentation Engineering from Seoul National University of Technology in 2005. Also, he received the M.S. degree in Mechatroncis Engineering from Korea University in 2007. His research interests include mobile robotics. Jae-Bok Song received the B.S. and M.S. degrees in Mechanical Engineering from Seoul National University in 1983 and 1985, respectively. Also, he received the Ph.D. degree in Mechanical Engineering from MIT in 1992. He is currently a Professor of Mechanical Engineering, Korea University, where he is also the Director of the Intelligent Robotics Laboratory from 1993. His current research interests lie mainly in mobile robotics, safe robot arms, and design/control of intelligent robotic systems.     

Generation of templates for low-resolution text recognition using a hypothesis graph

We propose a recognition method of character-string images captured by portable digital cameras. A challenging task in character-string recognition is the segmentation of characters. In the proposed method, a hypothesis graph is used for recognition-based segmentation of the character-string images. The hypothesis graph is constructed by the subspace method, using eigenvectors as conditionally elastic templates. To obtain these templates, a generation-based approach is introduced in the training stage. Various templates are generated to cope with low-resolution. We have experimentally proved that the proposed scheme achieves high recognition performance even for low-resolution character-string images. The text was submitted by the authors in English. Hiroyuki Ishida. Received his B.S. and M.S. degrees from the Department of Information Engineering and from the Graduate School of Information Science, respectively, at Nagoya University. He is currently pursuing a Ph.D. in Information Science at Nagoya University. Ichiro Ide. Received his B.S. degree from the Department of Electronic Engineering, his M.S. degree from the Department of Information Engineering, and his Ph.D. from the Department of Electrical Engineering at the University of Tokyo. He is currently an Associate Professor in the Graduate School of Information Science at Nagoya University. Tomokazu Takahashi. Received his B.S. degree from the Department of Information Engineering at Ibaraki University, and his M.S. and Ph.D. from the Graduate School of Science and Engineering at Ibaraki University. His research interests include computer graphics and image recognition. Hiroshi Murase. Received his B.S., M.S., and Ph.D. degrees from the Graduate School of Electrical Engineering at Nagoya University. He is currently a Professor in the Graduate School of Information Science at Nagoya University. He received the Ministry Award from the Ministry of Education, Culture, Sports, Science and Technology in Japan in 2003. He is a Fellow of the IEEE.     

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.     

Zikimi: A Case Study in Micro Kernel Design for Multimedia Applications

Due to recent rapid deployment of Internet Appliances and PostPC products, the importance of developing lightweight embedded operating system is being emphasized more. In this article, we like to present the details of design and implementation experience of low cost embedded system, Zikimi, for multimedia data processing. We use the skeleton of existing Linux operating system and develop a micro-kernel to perform a number of specific tasks efficiently and effectively. Internet Appliances and PostPC products usually have very limited amount of hardware resources to execute very specific tasks. We carefully analyze the system requirement of multimedia processing device. Weremove the unnecessary features, e.g. virtual memory, multitasking, a number of different file systems, and etc. The salient features of Zikimi micro kernel are (i) linear memory system and (ii) user level control of I/O device. The result of performance experiment shows that LMS (linear memory system) of Zikimi micro kernel achieves significant performance improvement on memory allocationagainst legacy virtual memory management system of Linux. By exploiting the computational capability of graphics processor and its local memory, we achieve 2.5 times increase in video processing speed. Supported by KOSEF through Statistical Research Center for Complex Systems at Seoul National University. Funded by Faculty Research Institute Program 2001, Sahmyook University, Korea. Sang-Yeob Lee received his B.S. and M.S degree from Hanyang University, seoul, Korea in 1995. He is currently working towards the Ph.D. degree in Devision of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. Since 1998, he has been on the faculty of Information Management System at Sahmyook university, Seoul, Korea. His research interests include robot vision systems, pattern recognition, Multimedia systems. He is a member of IEEE. Youjip Won received the B.S and M.S degree in Computer Science from the Department of Computer Science, Seoul National University, Seoul, Korea in 1990 and 1992, respectively and the Ph.D. in Computer Science from the University of Minnesota, Minneapolis in 1997. After finishing his Ph.D., He worked as Server Performance Analysts at Server Architecture Lab., Intel Corp. Since 1999, he has been on the board of faculty members in Division of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. His current research interests include Multimedia Systems, Internet Technology, Database and Performance Modeling and Analysis. He is a member of ACM and IEEE. Whoi-Yul Kim received his B.S. degree in Electronic Engineering from Hanyang University, Seoul, Korea in 1980. He received his M.S. from Pennsylvania State University, University Park, in 1983 and his Ph.D. from Purdue University, West Lafayette, in 1989, both in Electrical Engineering. From 1989 to 1994, he was with the Erick Jonsson School of Engineering and Computer Science at the University of Texas at Dallas. Since 1994, he has been on the faculty of Electronic Engineering at Hanyang University, Seoul, Korea. He has been involved with research development of various range sensors and their use in robot vision systems. Recently, his work has focused on content-based image retrieval system. He is a member of IEEE.     

A noise robust gait representation: Motion energy image

Gait-based human identification aims to discriminate individuals by the way they walk. A unique advantage of gait as a biometric is that it requires no subject contact and is easily acquired at a distance, which stands in contrast to other biometric techniques involving face, fingerprints, iris, etc. This paper proposes a new gait representation called motion energy image (MEI). Compared with other gait features, MEI is more robust against noise that can be included in binary gait silhouette images due to various factors. The effectiveness of the proposed method for gait recognition is demonstrated using experiments performed on the NLPR database. Recommended by Editorial Board member Jang Myung Lee under the direction of Editor Jae-Bok Song. This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. Grant Number: R11-2002-105-09002-0 (2009). Heesung Lee received the B.S. and M.S. degrees in Electrical and Electronic Engineering, from Yonsei University, Seoul, Korea, in 2003 and 2005, respectively. He is currently a Ph.D. candidate of Dept. of Electrical and Electronic Engineering at Yonsei University. His current research interests include computational intelligence, pattern recognition, biometrics, and neural network. Sungjun Hong received the B.S. degrees in Electrical and Electronic Engineering and Computer Science, from Yonsei University, Seoul, Korea, in 2005. He is a graduate student of the combined master’s and doctoral degree programs at Yonsei University. He has studied machine learning, biometrics and optimization Imran Fareed Nizami received the B.S. degree from University of Engg. & Tech. Taxila, Pakistan and the M.S. degree in the Electrical and Electronic Engineering from Yonsei University, Seoul, Korea. He is currently a senior lecturer in Bahria University, Islamabad, Pakistan. His research interests include biometrics, gait recognition, Bayesian and neural networks. Euntai Kim received the B.S. (with top honors), M.S. and Ph.D. degrees in Electronic Engineering from Yonsei University, Seoul, Korea, in 1992, 1994, and 1999, respectively. From 1999 to 2002, he was a Full-time Lecturer with the Department of Control and Instrumentation Engineering at Hankyong National University, Gyeonggi-do, Korea. Since 2002, he has been with the School of Electrical and Electronic Engineering at Yonsei University, where he is currently an associate professor. He was a Visiting Scholar with the University of Alberta, Edmonton, Canada, and the Berkeley Initiative in Soft Computing (BISC), UC Berkeley, USA, in 2003 and 2008, respectively. His current research interests include computational intelligence and machine learning and their application to intelligent service robots, unmanned vehicles, home networks, biometrics, and evolvable hardware.     

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

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.     

Real-time pinch detection algorithm: Robust to impulsive noise

A robust pinch detection algorithm which can be implemented in a cheap microprocessor is proposed for the development of a safety feature in the automotive power window system. To solve the problems caused by the performance degradation of a Hall sensor or real driving situations, the proposed algorithm makes use of the H _∞ state estimation technique. The motivation of this approach comes from the advantage that the H _∞ filter can minimize or bound the worst-case estimation error energy for all bounded energy disturbances. Herein, the pinch torque rate estimator is derived from applying the steady-state H _∞ filter to the augmented model, which includes the motor dynamics and an additional torque rate state. Then, to redesign an appropriate estimator for real-time implementation, the torque rate estimate can be calculated more efficiently than the previous method [1]. Experimental results verify that, with a small amount of computation, the proposed pinch detection algorithm provides fast pinch detection performance superior to the existing method. Furthermore, it guarantees robustness against the worst-case measurement noises. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Young Il Lee. Jung-Hoon Park received the B.E. degree in Electronic Engineering in 1996, and the M.S. degree in Electrical and Electronic Engineering from Yonsei University, Seoul, Korea, in 2002. He worked with Samsung Electronics as an Engineer from 1996 to 1999. He is currently pursuing his doctoral degree at Yonsei University. His research interests include robust control and filtering theory, robot vision, and its applications. Won-Sang Ra received the B.E., M.S., and Ph.D. degrees in Electrical and Electronics Engineering from Yonsei University, Seoul, Korea, in 1998, 2000, and 2009, respectively. From March 2000 to February 2009, he was with the Guidance and Control Department of Agency for Defense Development, Daejeon, as a Senior Researcher. Since March 2009, he has been with the School of Mechanical and Control Engineering, Handong Global University, where he is currently a Full-Time Instructor. His main research topic includes the robust filtering theory and its applications to autonomous vehicle guidance and control. Tae-Sung Yoon received the B.E., M.S., and Ph.D. degrees, in Electrical Engineering from Yonsei University, Seoul, Korea, in 1978, 1980, and 1988, respectively. He worked with the Department of Electrical Engineering at the 2nd Naval Academy, Jinhae, Korea, as a member of the teaching staff from 1980 to 1983. He worked with the Department of Electrical Engineering at Vanderbilt University, Nashville, as a Visiting Assistant Professor from 1994 to 1995. Since 1989, he has been with the Department of Electrical Engineering, Changwon National University, Changwon, Korea where he is currently a Professor. His research interests include robust filtering, mobile robotics, and time-frequency signal processing in instrumentation. Jin-Bae Park received the B.E. degree in Electrical Engineering from Yonsei University, Seoul, Korea, in 1977, and the M.S. and Ph.D. degrees in Electrical Engineering from Kansas State University, Manhattan, in 1985, and 1990, respectively. Since 1992, he has been with the Department of Electrical and Electronic Engineering, Yonsei University, where he is currently a Professor. His research interests include robust control and filtering, nonlinear control, mobile robotics, fuzzy logic control, neural networks, genetic algorithms, and Hadamard-transform spectroscopy. He has served as the Director for the Transactions of the Korean Institute of Electrical Engineers (1998–2003) and the Institute of Control, Automation, and Systems Engineers (1999–2003). He is currently the Editor-in-Chief for the International Journal of Control, Automation, and Systems.     

Development of cleaning robot system for live-line suspension insulator strings

A new cleaning robot system for suspension insulator strings was developed to prevent a power failure, which can have severe effects on the national industry and economy. Compared with existing cleaning robots using jets of water or water/air, this robot mechanism is superior in insulation as it uses a porcelain-clamping method, and is more useful in mountainous or salt damage areas by adopting a dry cleaning method without water. In addition, in order to increase its cleaning efficiency and to prevent arc generation under live-line conditions, a set of mechanized brush bristles and a voltage-balancing contactor are devised, respectively. Moreover, a manual device for its installation and removal is presented. We confirmed its effectiveness through experiments. Recommended by Editorial Board member Hyoukryeol Choi under the direction of Editor Jae-Bok Song. This work was supported by Electric Power Industry R&D Project performed by Ministry of Commerce, Industry and Energy in Korea. Joon-Young Park received the B.S. degree in Electrical Engineering in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1997 and 2004, respectively. He is now a Senior Researcher at the Strategic Technology Laboratory in Korea Electric Power Research Institute (KEPRI). His research interests include the robust control of nonlinear systems, the optimum kinematic design of robot manipulators as well as robot systems for the electric power industry. Byung-Hak Cho received the B.S. degree in Electrical Engineering from Hanyang University, Seoul, Korea, in 1982, and the M.S. and Ph.D. degrees in Nuclear Engineering from KAIST, Daejeon, Korea, in 1986 and 1996, respectively. He is now a Chief Researcher at the Strategic Tech-nology Laboratory in KEPRI, Daejeon, Korea. His research interests include robot systems for the electric power industry. Seung-Hyun Byun received the B.S. degree in Electrical Engineering from Yonsei University, Seoul, Korea, in 1992, and the M.S. degree in Electrical Engineering from KAIST, Daejeon, Korea, in 1994. He is now a Senior Researcher at the Power Generation Laboratory in KEPRI, Daejeon, Korea. His research interests include control system design, signal processing and artificial intelligence. Jae-Kyung Lee received the B.S. degree in Electrical Engineering from Kyungpook National University, Daegu, Korea, in 2002, and M.S. the degree in Electrical Engineering from KAIST, Daejeon, Korea, in 2004. He is now a Researcher at the Strategic Technology Laboratory in KEPRI, Daejeon, Korea. His research interests include the development of high-performance robot control and hazardous robot systems.     

Design and analysis of the Dual-Torus Network

In this paper, we propose a new topology called theDual Torus Network (DTN) which is constructed by adding interleaved edges to a torus. The DTN has many advantages over meshes and tori such as better extendibility, smaller diameter, higher bisection width, and robust link connectivity. The most important property of the DTN is that it can be partitioned into sub-tori of different sizes. This is not possible for mesh and torus-based systems. The DTN is investigated with respect to allocation, embedding, and fault-tolerant embedding. It is shown that the sub-torus allocation problem in the DTN reduces to the sub-mesh allocation problem in the torus. With respect to embedding, it is shown that a topology that can be embedded into a mesh with dilation δ can also be embedded into the DTN with less dilation. In fault-tolerant embedding, a fault-tolerant embedding method based on rotation, column insertion, and column skip is proposed. This method can embed any rectangular grid into its optimal square DTN when the number of faulty nodes is fewer than the number of unused nodes. In conclusion, the DTN is a scalable topology well-suited for massively parallel computation. Sang-Ho Chae, M.S.: He received the B.S. in the Computer Science and Engineering from the Pohang University of Science and Technology (POSTECH) in 1994, and the M.E. in 1996. Since 1996, he works as an Associate Research Engineer in the Central R&D Center of the SK Telecom Co. Ltd. He took part in developing SK Telecom Short Message Server whose subscribers are now over 3.5 million and Advanced Paging System in which he designed and implemented high availability concepts. His research interests are the Fault Tolerance, Parallel Processing, and Parallel Topolgies. Jong Kim, Ph.D.: He received the B.S. degree in Electronic Engineering from Hanyang University, Seoul, Korea, in 1981, the M.S. degree in Computer Science from the Korea Advanced Institute of Science and Technology, Seoul, Korea, in 1983, and the Ph.D. degree in Computer Engineering from Pennsylvania State University, U.S.A., in 1991. He is currently an Associate Professor in the Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea. Prior to this appointment, he was a research fellow in the Real-Time Computing Laboratory of the Department of Electrical Engineering and Computer Science at the University of Michigan from 1991 to 1992. From 1983 to 1986, he was a System Engineer in the Korea Securities Computer Corporation, Seoul, Korea. His major areas of interest are Fault-Tolerant Computing, Performance Evaluation, and Parallel and Distributed Computing. Sung Je Hong, Ph.D.: He received the B.S. degree in Electronics Engineering from Seoul National University, Korea, in 1973, the M.S. degree in Computer Science from Iowa State University, Ames, U.S.A., in 1979, and the Ph.D. degree in Computer Science from the University of Illinois, Urbana, U.S.A., in 1983. He is currently a Professor in the Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea. From 1983 to 1989, he was a staff member of Corporate Research and Development, General Electric Company, Schenectady, NY, U.S.A. From 1975 to 1976, he was with Oriental Computer Engineering, Korea, as a Logic Design Engineer. His current research interest includes VLSI Design, CAD Algorithms, Testing, and Parallel Processing. Sunggu Lee, Ph.D.: He received the B.S.E.E. degree with highest distinction from the University of Kansas, Lawrence, in 1985 and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1987 and 1990, respectively. He is currently an Associate Professor in the Department of Electronic and Electrical Engineering at the Pohang University of Science and Technology (POSTECH), Pohang, Korea. Prior to this appointment, he was an Associate Professor in the Department of Electrical Engineering at the University of Delaware in Newark, Delaware, U.S.A. From June 1997 to July 1998, he spent one year as a Visiting Scientist at the IBM T. J. Watson Research Center. His research interests are in Parallel, Distributed, and Fault-Tolerant Computing. Currently, his main research focus is on the high-level and low-level aspects of Inter-Processor Communications for Parallel Computers.     

Sliding mode control for trajectory tracking of mobile robot in the RFID sensor space

This paper presents a sliding mode control method for wheeled mobile robots. Because of the nonlinear and nonholonomic properties, it is difficult to establish an appropriate model of the mobile robot system for trajectory tracking. A robust control law which is called sliding mode control is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. The posture of the mobile robot (including the position and heading direction) is presented and the kinematics equations are established in the two-dimensional coordinates. According to the kinematics equations, the controller is designed to find an acceptable control law so that the tracking error will approximate 0 as the time approaches infinity with an initial error. The RFID sensor space is used to estimate the real posture of the mobile robot. Simulation and experiment demonstrate the efficacy of the proposed system for robust tracking of mobile robots. Recommended by Sooyong Lee under the direction of Editor Jae-Bok Song. This work was supported by the Korea Science and Engineering (KOSEF) grant funded by the Korea government (MOST) (No. R01-2007-000-10171-0). Jun Ho Lee received the M.S degree in Mechanical Engineering from Pusan National University. His research interests include factory automation and sliding mode control. Cong Lin received the B.S. degree in Electrical Engineering from Jilin University and the M.S degree in Electrical Engineering from Pusan National University. His research interests include neural network and sliding mode control. Hoon Lim is currently a M.S student in Electrical Engineering of Pusan National University. His research interests include mobile manipulator and sliding mode control. Jang Myung Lee received the B.S. and M.S degrees in Electronics Engineering from Seoul National University, Korea. He received the Ph.D. degree in Computer from the University of Southern California, Los Angeles. Now, he is a Professor in Pusan National University. His research interests include integrated manufacturing systems and intelligent control.     

Evolutionary fusion of a multi-classifier system for efficient face recognition

In this paper an evolutionary classifier fusion method inspired by biological evolution is presented to optimize the performance of a face recognition system. Initially, different illumination environments are modeled as multiple contexts using unsupervised learning and then the optimized classifier ensemble is searched for each context using a Genetic Algorithm (GA). For each context, multiple optimized classifiers are searched; each of which are referred to as a context based classifier. An evolutionary framework comprised of a combination of these classifiers is then applied to optimize face recognition as a whole. Evolutionary classifier fusion is compared with the simple adaptive system. Experiments are carried out using the Inha database and FERET database. Experimental results show that the proposed evolutionary classifier fusion method gives superior performance over other methods without using evolutionary fusion. Recommended by Guest Editor Daniel Howard. This work was supported by INHA UNIVERSITY Research Grant. Zhan Yu received the B.E. degree in Software Engineering from Xiamen University, China, in 2008. He is currently a master student in Intelligent Technology Lab, Computer and Information Department, Inha University, Korea. He has research interests in image processing, pattern recognition, computer vision, machine learning and statistical inference and computating. Mi Young Nam received the B.Sc. and M.Sc. degrees in Computer Science from the University of Silla Busan, Korea in 1995 and 2001 respectively and the Ph.D. degree in Computer Science & Engineering from the University of Inha, Korea in 2006. Currently, She is Post-Doctor course in Intelligent Technology Laboratory, Inha University, Korea. She’s research interest includes biometrics, pattern recognition, computer vision, image processing. Suman Sedai received the M.S. degree in Software Engineering from Inha University, China, in 2008. He is currently a Doctoral course in Western Australia University, Australia. He has research interests in image processing, pattern recognition, computer vision, machine learning. Phill Kyu Rhee received the B.S. degree in Electrical Engineering from the Seoul University, Seoul, Korea, the M.S. degree in Computer Science from the East Texas State University, Commerce, TX, and the Ph.D. degree in Computer Science from the University of Louisiana, Lafayette, LA, in 1982, 1986, and 1990 respectively. During 1982–1985 he was working in the System Engineering Research Institute, Seoul, Korea as a research scientist. In 1991 he joined the Electronic and Telecommunication Research Institute, Seoul, Korea, as a Senior Research Staff. Since 1992, he has been an Associate Professor in the Department of Computer Science and Engineering of the Inha University, Incheon, Korea and since 2001, he is a Professor in the same department and university. His current research interests are pattern recognition, machine intelligence, and parallel computer architecture. dr. rhee is a Member of the IEEE Computer Society and KISS (Korea Information Science Society).     

Swing-up control for an inverted pendulum with restricted cart rail length

In this paper, we propose a new swing-up strategy for cart inverted pendulums with restricted rail length. The proposed swing-up strategy is derived from a new Lyapunov function. The Lyapunov function is defined as the sum of the square of the pendulum energy and the weighted square of the cart’s velocity. The resulting swing-up strategy is represented in a compact form and has two design parameters. By adjusting these design parameters, we can affect the swing-up strategy such that the restriction on the rail length is satisfied. We also provide a state-dependent transformation to obtain voltage input to a DC motor required to generate the cart’s acceleration obtained from the proposed swing-up strategy. Finally, we illustrate the performance of the proposed swing-up law through simulation and experiments. It is shown that there is quite good correspondence between theory and experiments. Recommended by Editorial Board member Duk-Sun Shim under the direction of Editor Jae Weon Choi. This work was supported by an Inha Research Grant. Ji-Hyuk Yang received the M.Sc. degree in Electrical Engineering from Inha University, Inchon, Korea, in 2008. He is currently pursuing a Ph.D. degree in Electrical Engineering at Inha University, Inchon, Korea. His primary research interest lies in the development of rapid control prototyping environment. Su-Yong Shim received the B.Sc. degree in Electrical Engineering from Inha University, Inchon, Korea, in 2008. He is currently pursuing his M.Sc. degree in Electrical Engineering at Inha University, Inchon, Korea. His research interests are mechatronics and embedded systems. Jung-Hun Seo received the B.Sc. degree in Electrical Engineering from Inha University, Inchon, Korea, in 2008. He is currently pursuing his M.Sc. degree in Electrical Engineering at Inha University, Inchon, Korea. His research interests are mechatronics, embedded systems, and control applications. Young Sam Lee received the B.S. and M.S. degrees in Electrical Engineering from Inha University, Inchon, Korea in 1997 and 1999, respectively. He received the Ph.D. at the School of Electrical Engineering and Computer Science from Seoul National University, Seoul, Korea, in 2003. His research interests include time delay systems, receding horizon control, signal processing, and embedded systems. He is currently with the School of Electrical Engineering, Inha University, Incheon, Korea.     

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.     

Nonlinear adaptive decentralized stabilization control for multimachine power systems

This paper presents a decentralized adaptive backstepping controller to dampen oscillations and improve the transient stability to parametric uncertainties in multimachine power systems. The proposed design on the i ^th synchronous generator uses only local information and operates without the need for remote signals from the other generators. The design of the nonlinear controller is based on a modified fourth-order nonlinear model of a synchronous generator, and the automatic voltage regulator model is considered so as to decrease the steady state voltage error. The construction of both the control law and the associated Lyapunov function is systematically designed within the design methodology. A 3-machine power system is used to demonstrate the effectiveness of the proposed controller over two other controllers, namely a conventional damping controller (power system stabilizer) and one designed using the feedback linearization techniques. Recommended by Editorial Board member Gang Tao under the direction of Editor Jae Weon Choi. This work was supported by the Korea Electrical Engineering and Science Research Institute, which is funded by Ministry of Commerce, Industry and Energy. Shan-Ying Li received the B.S. degrees in Computer Science and M.S. degree in Electrical Engineering from Northeast DianLi University, China, in 1997 and 2002, respectively. She obtained the Ph.D. degree in Electrical Engineering from Seoul National University, Korea, in 2008. She is a Post Doctor in North China Electric Power Research Institute, North China Grid Co., Ltd., China. Her research interests are in the areas of advanced control and stability applications on power systems. Sang-Seung Lee received the M.S.E.E. and Ph.D. degrees in Electrical Engineering at Seoul National University. Currently, he is with Power System Research Division of KESRI, Seoul National University, Korea. His interest areas are nonlinear/adaptive control theory, North-East Asia power system interconnection, distributed/small generation, distributed transmission/distribution load flow algorithm, regional/local energy system, PSS (power system stabilizer), and RCM (Reliability Centered Maintenance). Yong Tae Yoon was born in Korea on April 20, 1971. He received the B.S. degree, M.Eng. and Ph.D. degrees from M.I.T., USA in 1995, 1997, and 2001, respectively. Currently, he is an Assistant Professor in the School of Electrical Engineering and Computer Science at Seoul National University, Korea. His special field of interest includes electric power network economics, power system reliability, and the incentive regulation of independent transmission companies. Jong-Keun Park received the B.S. degree in Electrical Engineering from Seoul National University, Seoul, Korea in 1973 and the M.S. and Ph.D. degrees in Electrical Engineering from The University of Tokyo, Japan in 1979 and 1982, respectively. He is currently a Professor of School of Electrical Engineering, Seoul National University. In 1992, he attended as a Visiting Professor at Technology and Policy Program and Laboratory for Electromagnetic and Electronic Systems, Massachusetts Institute of Technology. He is a Senior Member of the IEEE, a Fellow of the IEE, and a Member of Japan Institute of Electrical Engineers (JIEE).     

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.     

Robust control design of a class of nonlinear systems in polynomial lower-triangular form

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.