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American control Conference (ACC)

作者： Dandan Zhang Long Wang Junzhi Yu Intelligent Control Laboratory Center for Systems and Control Department of Mechanics and Space Technologies College of Engineering Peking University Beijing China Laboratory of Complex Systems and Intelligent Science Institute of Automation Chinese Academy and Sciences Beijing China

This paper gives a coordination method for multiple biomimetic robotic fish in underwater transport task. Considering the inherent kinematic constraints of the robotic fish, and the unstructured and dynamic characteristics of the water environment, the limit cycle approach is utilized to control the posture of the fish, and realize collision avoidance. To control the transport orientation in the particular underwater environment, fuzzy logic method is adopted. Experimental results performed by three robotic fish validate the effectiveness of the proposed method.

关键词： Biomimetics Robot kinematics Marine animals Collision avoidance Propulsion Robotics and automation Fluid flow control Limit-cycles Fuzzy logic Educational institutions

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LPV control for the Air Path System of Diesel Engines

LPV Control for the Air Path System of Diesel Engines

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International Conference on control and automation (ICCA)

作者： Lihua Liu Xiukun Wei Xiaohe Liu Department of Computer Science and Automation Beijing Institute of Machinery Beijing China Delft Center for Control and Systems Delft University of Technnology Delft Netherlands

This paper addresses the gain scheduled H infin control issue for the air path system of diesel engines. The air path system is modeled as a linear parameter varying (LPV) system, where the system matrices are dependent on two exogenous variables: the engine speed and the turbine vane position. The open loop frequency property is presented as well as the detailed synthesis procedure of the gain scheduled controller such as the weighting function selection and design. A comparative study between the gain scheduled LPV control and the H infin control is investigated. Simulation results are shown to demonstrate the effectiveness of the gain scheduled LPV controller.

关键词： control systems Diesel engines Job shop scheduling Open loop systems control system synthesis Automatic control automation Nonlinear control systems computer science Machinery

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Teleoperation System of the Internet-based Omnidirectional Mobile Robot with A Mounted Manipulator

Teleoperation System of the Internet-based Omnidirectional M...

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IEEE International Conference on Mechatronics and automation

作者： Dawei Wang Jianqiang Yi Dongbin Zhao Guosheng Yang Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Institute of Advanced Control and Intelligent Information Processing College of Computer and Informaion Engineering Henan University Kaifeng China

A platform of the Internet-based teleoperation system with an omni-directional mobile robot which has a five DOFs robot arm is constructed. Remote control of the robot through the Internet is implemented. The system is featured as low-cost and user interface friendly: remote users can control the robot through the Internet just by a client program in a general computer. The client computer can receive the live video and environment information measured by sensors. With the help of the remote video and the local simulation, users can easily communicate with the robot. Different modules are proposed and the implementation method of the system is presented. Related experiments are conducted to test the validity of the proposed system.

关键词： Internet Mobile robots Manipulators Robot sensing systems Robot control User interfaces control systems computer interfaces Computational modeling System testing

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Construction of Expanded Input Space for Modeling Hysteretic systems

Construction of Expanded Input Space for Modeling Hysteretic...

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IEEE International Symposium on Intelligent control (ISIC)

作者： Y. Tan X. Zhao Laboratory of Intelligent Systems and Control Engineering Guilin University of Electronic and Technology Guilin China Institute of Automation Zhejiang Science and Technology University China

A neural model for hysteresis based on expanded input space is proposed in this article. In this method, the behavior of hysteresis is considered as a dynamic system that can be described by a nonlinear state space equation containing hysteretic state. In order to transfer the multi-valued mapping of hysteresis into a one-to-one mapping, an expanded input space involving the original input variable and a so-called Duhem operator is constructed. Thus, the neural networks can be employed to approximate the relation between the hysteretic state and the output of the system that is also the output of hysteresis. The proposed model has a simple architecture that can be easily implemented for on-line adaptation for the model in case of the unexpected change of operating environment. Furthermore, the dynamic performance of the model is improved because of the existence of Duhem operator. Finally, the method is used to the modeling of hysteresis in a piezoelectric actuator.

关键词： Hysteresis Nonlinear equations Intelligent actuators control system synthesis Nonlinear dynamical systems Neural networks Intelligent control Real time systems Nonlinear systems State-space methods

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A Note on Minimal Positive Realizations of Continuous-Time Linear systems

A Note on Minimal Positive Realizations of Continuous-Time L...

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IEEE International Conference on Networking, Sensing and control

作者： Yuwei Sun Wensheng Yu Long Wang Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Center for Systems and Control Department of Mechanics and Engineering Sciences Peking University Beijing China

We mainly discuss minimal positive realizations of nth-order rational transfer functions of continuous-time linear time-invariant single-input-single-output (SISO) systems and provide conditions for these systems to have positive realizations of the same order. The results obtained can aid in deciding the minimal compartment number of a compartmental system, finding a representation for a phase type (PH) distribution. One numerical example is employed to validate the results.

关键词： Linear systems Transfer functions control systems Sun Optical design Signal design Microwave filters Nonlinear filters Optical filters Educational technology

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MODELING AND control OF ELEVATORS BY STATECHARTS

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Asian Journal of control 2008年第2期6卷

作者： Yi-Sheng Huang Sheng-Luen Chung Mu-Der Jeng Department of Aeronautical Engineering Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit

Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.

关键词： Statechart interactive systems elevator

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Foundation of Notation and Classification of Nonconventional Static and Dynamic Neural Units

Foundation of Notation and Classification of Nonconventional...

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IEEE International Conference on Cognitive Informatics

作者： Ivo Bukovsky Zeng-Guang Hou Jiri Bila Madan M. Gupta Department of Instrumentation and Control Engineering Czech Technical University Czech Republic Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences China Intelligent Systems Research Laboratory College of Engineering University of Saskatchewan Canada

The paper introduces basic types of nonconventional artificial neural units and focuses their notation and classification: namely; the notation and classification of dynamic higher-order nonlinear neural units, time-delay dynamic neural units, and time-delay higher-order nonlinear neural units is introduced. Brief introduction into the simplified parallel of higher-order nonlinear aggregating function of artificial nonconventional neural units and synaptic and somatic operation of biological neurons is made. Based on still simplified mathematical notation, it is proposed that nonlinear aggregating function of neural inputs should be understood as composition of synaptic as well as partial somatic neural operation also for static neural units. Thus it unravels novel, simplified, yet universal insight into understanding more computationally powerful neurons. The classification of nonconventional artificial neural units is founded first according to nonlinearity of aggregating function, second according to the dynamic order, third according to time-delay implementation within neural units.

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Stable PD and Internal Force control of Omnidirectional Wheeled Mobile Manipulators

Stable PD and Internal Force Control of Omnidirectional Whee...

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IEEE International Conference on Mechatronics and automation

作者： Dong Xu Dongbin Zhao Jianqiang Yi Xuyue Deng Guosheng Yang Key Lab of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Institute of Advanced Control and Intelligent Information Processing College of Computer and Information Engineering Henan University Kaifeng China

Omnidirectional mobile manipulator, which is composed by a three DOF omnidirectional mobile platform and a mounted manipulator, can move in any direction at any time. By reason of the redundantly actuated mechanism, the omnidirectional motion property of the mobile platform is similar to the parallel manipulator cooperatively manipulating objects, which admits internal force doing none contribution to the motion of the platform. Thus, the internal force should be controlled to reduce energy waste. Therefore, a stable PD controller is developed first for motion control of the integrated mobile manipulator system. Then, by treating the motion induced force as disturbance, a feed forward plus PI type force controller is addressed to regulate the internal force to zero. Finally, simulation results demonstrate the validity of the proposed approach.

关键词： Force control Motion control Wheels Kinematics Manipulator dynamics automation control systems Intelligent actuators Centralized control Mechatronics

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LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR control

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Asian Journal of control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

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Particle Swarn Optimized Adaptive Dynamic Programming

Particle Swarn Optimized Adaptive Dynamic Programming

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IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Dongbin Zhao Jianqiang Yi Derong Liu Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA

Particle swarm optimization is used for the training of the action network and critic network of the adaptive dynamic programming approach. The typical structures of the adaptive dynamic programming and particle swarm optimization are adopted for comparison to other learning algorithms such as gradient descent method. Besides simulation on the balancing of a cart pole plant, a more complex plant pendulum robot (pendubot) is tested for the learning performance. Compared to traditional adaptive dynamic programming approaches, the proposed evolutionary learning strategy is verified as faster convergence and higher efficiency. Furthermore, the structure becomes simple because the plant model does not need to be identified beforehand

关键词： Dynamic programming Particle swarm optimization Neural networks Robots Backpropagation Adaptive systems Evolutionary computation Learning Cost function Testing

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