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International Conference on Intelligent Computation Technology and Automation, ICICTA

作者： Lingfei Wu Max Q.-H. Meng Zhenzhong Dong Huawei Liang Department of Automation University of Science and Technology Hefei Anhui China Center of Biomimetic Sensing and Control Research Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China Department of Computer Science University of Science and Technology Hefei Anhui China

ISBN: (纸本)9781424447411

Node localization is an important problem for location-dependent applications of wireless sensor networks. Aiming at the positioning problem of wireless sensor networks node location, an improved DV-Hop localization algorithm is proposed in this paper. The proposed method firstly recalculates the hop-size and sends different correction along different directions instead of computing a single correction to be broadcasted into the networks. Then we empirically evaluate the difference between distance estimate and actual distance through a number of simulation experiments statistical results. We find empirical parameter to improve the accuracy of distance estimate. Simulation results show that the performance of the proposed scheme outweighs classical DV-Hop algorithms, especially in lower connectivity.

关键词： Wireless sensor networks Intelligent sensors computer networks Intelligent networks Machine intelligence Biomimetics Intelligent robots Robotics and automation Broadcasting Computational modeling

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Multi-Innovation Stochastic Gradient Algorithm for Output Error Systems Based on the Auxiliary Model

Multi-Innovation Stochastic Gradient Algorithm for Output Er...

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2009 American control Conference (ACC 2009)

作者： Dongqing Wang Feng Ding Peter X. Liu College of Automation Engineering Qingdao University (Jiangnan University) Qingdao P.R. China 266071 Control Science and Engineering Research Center at the Jiangnan University Wuxi P.R. China 214122 Department of Systems and Computer Engineering Carleton University Ottawa Canada K1S 5B6

ISBN: (纸本)9781424445233

This paper combines the multi-innovation theory with the auxiliary model identification idea to present the auxiliary model based multi-innovation stochastic gradient algorithm by expanding the scalar innovation to an innovation vector and introducing the innovation length. Convergence analysis in the stochastic framework indicates that the parameter estimation error consistently converges to zero under certain excitation condition. Finally, we illustrate and test the proposed algorithm with an example.

关键词： Stochastic systems Convergence Educational institutions Stochastic processes Technological innovation Parameter estimation Least squares methods Covariance matrix Computational complexity White noise

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∞ model reduction for linear parameter-varying systems with distributed delay

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International Journal of control 2009年第3期82卷 408-422页

作者： Ligang Wu Peng Shi Huijun Gao & Junling Wang Space Control and Inertial Technology Research Center Harbin Institute of Technology Harbin 150001 P. R. China Faculty of Advanced Technology University of Glamorgan Pontypridd CF3 1DL UK Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada College of Nuclear Science and Technology Harbin Engineering University Nantong Street 145 Harbin 150001 China

This paper is concerned with the ∞ model reduction for linear parameter-varying (LPV) systems with both discrete and distributed delays. For a given stable system, our attention is focused on the construction of reduced-order models, which approximate the original system well in an ∞ norm sense. First, a sufficient condition is proposed for the asymptotic stability with an ∞ performance of the error system by using the parameter-dependent Lyapunov functional method. Then, the decoupling technique is applied, such that there does not exist any product term between the Lyapunov matrices and the system matrices in the parametrised linear matrix inequality (PLMI) constraints; thus a new sufficient condition is obtained. Based on the new condition, two different approaches are developed to solve the model reduction problem. One is the convex linearisation approach and the other is the projection approach. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed design method

关键词： Distributed delay model reduction parameterised linear matrix inequality (PLMI) linear parameter-varying (LPV) systems

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An adaptive particle swarm method to multiple dimensional problems

An adaptive particle swarm method to multiple dimensional pr...

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IASTED International Symposium on Computational Biology and Bioinformatics, CBB 2008

作者： Chen, Cheng-Hung Bosworth, Ken W. Schoen, Marco P. Department of Biological Sciences Measurement and Control Engineering Research Center College of Engineering Pocatello ID 83209 United States Department of Computer Science Measurement and Control Engineering Research Center College of Engineering Pocatello ID 83209 United States Department of Mechanical Engineering Measurement and Control Engineering Research Center College of Engineering Pocatello ID 83209 United States

ISBN: (纸本)9780889867741

The basic Particle Swarm Optimization (PSO) algorithm has exhibited good performance across a wide set of application problems. Nevertheless, an effective adaptive PSO method is still needed for multi-dimensional problems. This work presents an adaptive PSO (APSO) approach based on altering the maximum velocity at each iteration. Two thirty-dimensional benchmark problems are used in this study and a respectable performance is shown by the proposed PSO for the both problems.

关键词： Fuzzy logic

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Multi-task Coalition Parallel Formation Strategy Based on Reinforcement Learning

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自动化学报 2008年第3期34卷 349-352页

作者： JIANG Jian-Guo SU Zhao-Pin QI Mei-Bin ZHANG Guo-Fu Department of Computer and Information Science Hefei University of TechnologyHefei 230009P.R.China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of EducationHefei 230009P.R.China

代理人联盟是代理人协作和合作的一种重要方式。形成一个联盟，代理人能提高他们的能力解决问题并且获得更多的实用程序。在这份报纸，新奇多工联盟平行形成策略被介绍，并且多工联盟形成的过程是一个 Markov 决定过程的结论理论上被证... 详细信息

代理人联盟是代理人协作和合作的一种重要方式。形成一个联盟，代理人能提高他们的能力解决问题并且获得更多的实用程序。在这份报纸，新奇多工联盟平行形成策略被介绍，并且多工联盟形成的过程是一个 Markov 决定过程的结论理论上被证明。而且，学习的加强被用来解决多工联盟平行的代理人行为策略，和这个过程形成被描述。在多工面向的领域，策略罐头有效地并且平行形式多工联盟。

关键词：强化学习多任务合并平行排列马尔可夫决策过程

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A study of Particle Swarm Optimization on leukocyte adhesion molecules and control strategies for smart prosthetic hand

A study of Particle Swarm Optimization on leukocyte adhesion...

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IEEE Swarm Intelligence Symposium, SIS

作者： Cheng-Hung Chen Ken W. Bosworth Marco P. Schoen Shawn E. Bearden D. Subbaram Naidu Alba Perez Measurement and Control Engineering Research Center and the Department of Biological Sciences Idaho State University ID USA Measurement and Control Engineering Research Center and the Department of Computer Science Idaho State University ID USA Measurement and Control Engineering Research Center and the Department of Mechanical Engineering Idaho State University ID USA Idaho Biomedical Research Institute and the Department of Biological Sciences Idaho State University ID USA Measurement and Control Engineering Research Center and the Department of Electrical Engineering Idaho State University ID USA Measurement and Control Engineering ResearchCenter and the Department of Mechanical Engineering Idaho State University ID USA

Hard computing based optimization algorithms usually require a lot of computational resources and generally do not have the ability to arrive at the global optimum solution. Soft computing algorithms on the other hand negate these deficiencies, by allowing for reduced computational loads and the ability to find global optimal solutions, even for complex cost surfaces. This paper presents two numerical case studies where a particle swarm optimization (PSO) algorithm is applied to biomedical problems. In particular, the problem of identifying the rupture force for leukocyte adhesion molecules and the problem of finding the correct control parameters of a robotic hand, are addressed. Simulation results indicate that PSO is a feasible alternative to the computational expensive hard computing algorithms.

关键词： Particle swarm optimization White blood cells Adhesives Prosthetic hand Biomedical computing Cams Blood vessels Microorganisms Immune system Humans

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Sequential flocking control system for multiple mobile robots

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Kongzhi Lilun Yu Yingyong/control Theory and Applications 2008年第6期25卷 1117-1120+1127页

作者： Cheng, Lei Yu, Hui Wu, Huai-Yu Wang, Yong-Ji Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan University of Science and Technology Wuhan 430081 China Institute of Nonlinear and Complex Systems Three Gorges University Yichang 443002 China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Flocking control is a new type of control which coordinates the motions among multiple mobile robots. Current researches focus their attention on leaderless flocking controller design. We, in this paper, present the design of a sequential flocking control for multiple mobile robots, and put forward the corresponding performance evaluation method. Firstly, we briefly review the existing theories of agent-based sequential formation control;and then, transfer the agent-based flocking control strategy to the design of overall control algorithm for mobile robots, by considering the dynamics of nonholonomic mobile robot. To analyze the sequential flocking system, a flocking performance analysis method based on the least stability time (LST) is proposed. Simulations of real problems illustrate the processes of control and analysis of a multiple mobile robots sequential flocking system. The simulation results demonstrate the efficacy of our proposed procedure.

关键词： Mobile robots

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HLS parameter estimation for multi-input multi-output systems

HLS parameter estimation for multi-input multi-output system...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Ping Yuan Feng Ding Peter X. Liu Control Science and Engineering Research Center Jiangnan University Wuxi China Department of Systems and Computer Engineering Carleton University Ottawa Canada

In order to reduce computational burden of identification methods for multivariable systems, a hierarchical least squares (HLS) algorithm is developed. The basic idea is to use the hierarchical identification principle to decompose the identification model of the multivariable system into several submodels with smaller dimensions and fewer variables, and then to identify the parameter vector of each submodel. The analysis indicates that the parameter estimation error given by the proposed algorithm converges to zero under the persistent excitation. Also, the algorithm has much less computational efforts than the recursive least squares algorithm and is easy to implement on computer. Finally, we test the proposed algorithm by an example.

关键词： High level synthesis Parameter estimation MIMO Least squares approximation Least squares methods Polynomials Robotics and automation USA Councils Algorithm design and analysis computer errors

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Energy Efficient Data Transmission Mechanism in Wireless Sensor Networks

Energy Efficient Data Transmission Mechanism in Wireless Sen...

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International Symposium on computer science and Computational Technology, ISCSCT

作者： Na Xia Mei Tang Jian-guo Jiang Dun Li Hao-wei Qian Department of Computer and Information Hefei University of Technology China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei China

In wireless sensor networks, data transmission is an essential step for various applications, and an energy efficient data transmission mechanism is needed since the energy resource of WSN is restricted. This paper investigates the coalition-based cooperative data transmission mechanism (CC-DTM), analyzes its entire energy consumption, and finds out the optimal number of sensor nodes needed in the cooperative data transmission. The condition under which CC-DTM is more energy-saving than the cluster approach is also deduced. Furthermore, an energy-load balanced node selection strategy is proposed. The results of simulation experiment show the validity of this energy efficient data transmission mechanism.

关键词： Energy efficiency Data communication Wireless sensor networks Energy consumption computer networks Educational technology Broadcasting Energy measurement Batteries computer science

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