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American control Conference

作者： Lin Zhao Yingmin Jia Junping Du Jun Zhang Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479932757

In this paper, an adaptive output feedback tracking control scheme is proposed for spacecraft formation flying (SFF) in the presence of external disturbances, uncertain system parameters, input constraints and partial loss of control effectiveness. The proposed controller incorporates a pseudo-velocity filter to account for the unmeasured relative velocity, and the neural network (NN) technique is implemented to approximate the desired nonlinear function and bounded external disturbances. In order to guarantee that the output of the NN used in the controller is bounded by the corresponding bound of the approximated nonlinear function, a switch function is employed to generate a switching between the adaptive NN control and the robust controller. Moreover, a fault tolerant part is included in the controller to compensate the partial loss of actuator effectiveness fault. It is shown that the derived controller not only guarantees the tracking error in the closed-loop system to be uniformly ultimately bounded (UUB) but also ensures the control input can rigorously enforce actuator magnitude constraints. Simulation results are provided to demonstrate the effectiveness of the proposed method.

关键词： SFF UUB NN

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Robust H_∞ Consensus control of Uncertain Multi-Agent Systems with Nonlinear Dynamics and Time-Varying Delays

Robust H_∞ Consensus Control of Uncertain Multi-Agent Syste...

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American control Conference

作者： Ping Wang Yingmin Jia Junping Du Jun Zhang Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479932757

This paper is concerned with the H_∞ consensus control problem in undirected networks of autonomous agents with nonlinear dynamics, subject to parameter uncertainties and external disturbances. With the consideration of time-varying delays arising from communication among agents, a distributed protocol is proposed using the local delayed state information. Then, by defining an appropriate controlled output function, the consensus problem under the proposed protocol is converted into an H_∞ control problem. Based on robust H_∞ theory, sufficient conditions are derived to make all agents achieve consensus with desired H_∞ performance. Moreover, the feedback matrix in the proposed protocol is determined by solving two linear matrix inequalities (LMIs) with the same dimensions as a single agent. Finally, a numerical simulation is provided to demonstrate the effectiveness of our theoretical results.

关键词： Multi-agent systems Protocols Nonlinear dynamical systems Uncertain systems Linear matrix inequalities Robustness Delay effects

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Cooperative Bicircular Target Tracking Using Multiple Unmanned Aerial Vehicles

Cooperative Bicircular Target Tracking Using Multiple Unmann...

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IEEE Annual Conference on Decision and control

作者： Yueqian Liang Yingmin Jia Junping Du Fumitoshi Matsuno Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China Department of Mechanical Engineering and Science Kyoto University Kyoto 606-8501 Japan

ISBN: (纸本)9781467360890

This paper investigates the problem of tracking a moving target using multiple fixed-wing unmanned aerial vehicles (UAVs) under a new bicircular formation. This new formation for cooperative standoff target tracking is first developed by maximizing the amount of Fisher information. Guidance vector fields are designed, and based on them, a cooperation approach is proposed to adapt the unknown target velocity and achieve the cooperative bicircular tracking. Speed and heading rate are firstly controlled to track the guidance vector fields separately for each UAV, then the speed is further adjusted to maintain the desired angular separation between the UAVs. Simulation experiments are given to verify the effectiveness of the proposed approach.

关键词： bicircular Target tracking vehicle

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Erratum to: The whole genome sequence of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), reveals insights into the biology and adaptive evolution of a highly invasive pest species

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Genome biology 2017年第1期18卷 11页

作者： Alexie Papanicolaou Marc F Schetelig Peter Arensburger Peter W Atkinson Joshua B Benoit Kostas Bourtzis Pedro Castañera John P Cavanaugh Hsu Chao Christopher Childers Ingrid Curril Huyen Dinh HarshaVardhan Doddapaneni Amanda Dolan Shannon Dugan Markus Friedrich Giuliano Gasperi Scott Geib Georgios Georgakilas Richard A Gibbs Sarah D Giers Ludvik M Gomulski Miguel González-Guzmán Ana Guillem-Amat Yi Han Artemis G Hatzigeorgiou Pedro Hernández-Crespo Daniel S T Hughes Jeffery W Jones Dimitra Karagkouni Panagiota Koskinioti Sandra L Lee Anna R Malacrida Mosè Manni Kostas Mathiopoulos Angela Meccariello Monica Munoz-Torres Shwetha C Murali Terence D Murphy Donna M Muzny Georg Oberhofer Félix Ortego Maria D Paraskevopoulou Monica Poelchau Jiaxin Qu Martin Reczko Hugh M Robertson Andrew J Rosendale Andrew E Rosselot Giuseppe Saccone Marco Salvemini Grazia Savini Patrick Schreiner Francesca Scolari Paolo Siciliano Sheina B Sim George Tsiamis Enric Ureña Ioannis S Vlachos John H Werren Ernst A Wimmer Kim C Worley Antigone Zacharopoulou Stephen Richards Alfred M Handler Hawkesbury Institute for the Environment Western Sydney University Sydney Australia. Justus-Liebig-University Giessen Institute for Insect Biotechnology 35394 Giessen Germany. Department of Biological Sciences Cal Poly Pomona Pomona CA 91768 USA. Department of Entomology and Center for Disease Vector Research University of California Riverside Riverside CA 92521 USA. Interdepartmental Graduate Program in Genetics Genomics & Bioinformatics University of California Riverside Riverside CA 92521 USA. Department of Biological Sciences University of Cincinnati Cincinnati OH 45221 USA. Insect Pest Control Laboratory Joint FAO/IAEA Programme of Nuclear Techniques in Food and Agriculture Seibersdorf Vienna Austria. Department of Environmental and Natural Resources Management University of Patras Agrinio Greece. Department of Environmental Biology Centro de Investigaciones Biológicas CSIC 28040 Madrid Spain. Human Genome Sequencing Center Department of Human and Molecular Genetics Baylor College of Medicine 77030 Houston TX USA. National Agricultural Library USDA 20705 Beltsville MD USA. Georg-August-Universität Göttingen Johann-Friedrich-Blumenbach-Institut für Zoologie und Anthropologie 37077 Göttingen Germany. Department of Biology University of Rochester 14627 Rochester NY USA. Department of Biological Sciences Wayne State University 48202 Detroit MI USA. Department of Biology and Biotechnology University of Pavia 27100 Pavia Italy. USDA-ARS Pacific Basin Agricultural Research Center 96720 Hilo HI USA. DIANA-Lab Department of Electrical & Computer Engineering University of Thessaly 382 21 Volos Greece and Hellenic Pasteur Institute 11521 Athens Greece. Department of Entomology University of Illinois at Urbana-Champaign 61801 Urbana IL USA. Department of Biological Sciences Oakland University 48309 Rochester MI USA. Department of Biochemistry and Biotechnology University of Thessaly Larissa Greece. Department of Biology Univer

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Experimental Testing of a Traction control System with On-line Road Condition Estimation for Electric Vehicles

Experimental Testing of a Traction Control System with On-li...

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Mediterranean Conference on control & Automation

作者： Goran Vasiljevic Karlo Griparic Stjepan Bogdan LARICS - Laboratory for Robotics and Intelligent Control Systems Department of Control and Computer Engineering. Faculty of Electrical Engineering and Computing University of Zagreb

ISBN: (纸本)9781479909964

In this paper experimental results of testing slip-based traction control system (TCS) with an on-line road condition estimation are presented. TCS is designed for a car with in-wheel electric motors, so that estimation and control are implemented independently for each wheel thus enabling the optimal friction coefficient for every wheel, even if they are on different surfaces or have different tire characteristics. A road condition is approximated using a function which is estimated in the real-time and used as the input to the TCS. The design of the presented TCS is based on the wheel slip ratio, controlled to it's optimal value by a PI controller and with the addition of a feedforward branch for the transition response speed up. System is tested on a newly developed experimental setup consisting of the wheel with embedded (in-wheel) motor rolling on the metal drum loaded by the second motor simulating car behaviour.

关键词： Traction control Systems Pavement condition Electric vehicles Wheels PI control coefficient of friction experimental test SLIP RATIO Cars Best value IN-LINE

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Path planning for localization of an RF source by multiple UAVs on the Crammer-Rao Lower Bound

Path planning for localization of an RF source by multiple U...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Seyyed M. Mehdi Dehghan Mohammad Saberi Tavakkoli Hadi Moradi Advanced Robotics and Intelligent Systems laboratory Control and Intelligent Processing Center School of Electrical and Computer Engineering University of Tehran Tehran Iran

This paper presents a path planning approach of several UAVs for Radio Frequency (RF) source localization in None Line Of Sight (NLOS) propagation condition using the Received Signal Strength Indication (RSSI). The paths are planned such that the lower bound of standard deviation of localization error, which is equivalent to the Cramer-Rao Lower Bound (CRLB) of the estimation, minimized at any time. Due to the complexity of Jacobin calculation to perform global CRLB optimization, the local values of CRLBs in the current waypoint and next probable waypoints are used in the steepest decent approach to determine the best path. Furthermore, the complexity is reduced by discretizing the space for UAVs to make the computation feasible. The effect of NLOS propagation on the RSSI measurements is simulated by a log-normal distribution and the last estimation of radio source location is used to calculate the local CRLBs. The proposed approach has been simulated and compared with the basic bio-inspired approach of going toward the sensed direction of the source. The result shows better performance than the basic approach.

关键词： Jacobian matrices Noise

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A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition

A multi-step Gaussian filtering approach to reduce the effec...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Seyyed M. Mehdi Dehghan Hadi Moradi Advanced Robotics and Intelligent Systems laboratory Control and Intelligent Processing Center School of Electrical and Computer Engineering University of Tehran Tehran Iran

The hybrid localization using Angle of Arrival (AOA) and Received Strength Signal Indicator (RSSI) of an RF source, such as a cell phone in a search and rescue mission, with unknown power and None Line Of Sight (NLOS) condition have been proven to be advantageous compared to using each method separately. The hybrid approach has been proposed to benefit from both RSSI and AOA measurements. In this paper, the initial hybrid method, which was implemented using particle filters due to the multi-modal/non-Gaussian nature of localization in NLOS condition, has been replaced by a multi-step Gaussian filtering approach which provides nearly similar accuracy with better performance. The proposed method has been implemented using extended Kalman filter and Unscented Kalman filter. The simulation results show that the multi-step Gaussian filtering is comparable to particle filter in all cases with better performance. For further evaluation, the effects of uncertainty in the propagation parameters have been studied to show the robustness of each filter to these uncertainties.

关键词： Shadow mapping Atmospheric measurements Particle measurements Scattering Measurement uncertainty Particle filters Equations

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Underwater Target Positioning with a Single Acoustic Sensor

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IFAC Proceedings Volumes 2013年第33期46卷 233-238页

作者： D. Moreno-Salinas A.M. Pascoal J. Aranda Department of Computer Science and Automatic Control National University Distance Education (UNED) Spain Laboratory of Robotics and Systems in Engineering and Science (LARSyS) Instituto Superior Tecnico (IST) University of Lisbon Portugal Adjunct Scientist National Institute of Oceanography (NIO) Goa India

The availability of reliable underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or an autonomous surface vessel is key to the operation of some classes of AUVs. Furthermore, there is considerable interest in reducing the number of sensors involved in acoustic navigation/positioning systems to reduce the costs involved and the time consumed in the deployment, callibration, and recovery phases. Motivated by these considerations, in this paper we address the problem of single underwater target positioning based on measurements of the ranges between the target and a moving sensor at the sea surface, obtained via acoustic ranging devices. In particular, and speaking in loose terms, we are interested in determining the optimal geometric trajectory of the surface sensor that will, in a well defined sense, maximize the range-related information available for underwater target positioning. To this effect, an appropriate Fisher Information Matrix is defined and its determinant is maximized to yield the sensor trajectory that maximizes the accuracy of the target position estimate that can possibly be obtained with any unbiased estimator. It is shown that the optimal trajectory depends on the relative velocity of the sensor, the sampling time between measurements, and the number of measurements acquired for the FIM computation. Simulation examples illustrate the key results derived.

关键词： Autonomous Vehicles Underwater Navigation Optimal Sensor Placement Positioning Fisher Information Matrix Cramer-Rao Bound

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An energy harvester combining a piezoelectric cantilever and a single degree of freedom elastic system

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2012年第7期13卷 526-537页

作者： Hong-yan WANG Xiao-biao SHAN Tan XIE State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001China College of Computer and Control Engineering Qiqihar UniversityQiqihar 161006China

This paper presents a type of vibration energy harvester combining a piezoelectric cantilever and a single degree of freedom (SDOF) elastic system. The main function of the additional SDOF elastic system is to magnify vibration displacement of the piezoelectric cantilever to improve the power output. A mathematical model of the energy harvester is developed based on Hamilton's principle and Rayleigh-Ritz method. Furthermore, the effects of the structural parameters of the SDOF elastic system on the electromechanical outputs of the energy harvester are analyzed numerically. The accuracy of the output performance in the numerical solution is identified from the finite element method (FEM). A good agreement is found between the numerical results and FEM results. The results show that the power output can be increased and the frequency bandwidth can be improved when the SDOF elastic system has a larger lumped mass and a smaller damping ratio. The numerical results also indicate that a matching load resistance under the short circuit resonance condition can obtain a higher current output, and so is more suitable for application to the piezoelectric energy harvester.

关键词： Piezoelectric cantilever Single degree of freedom elastic （SDOF） system Energy harvesting Finite element analysis（FEA）

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Using general sound descriptors for early autism detection

Using general sound descriptors for early autism detection

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Asian control Conference

作者： Seyyed Hamid R. Ebrahimi Motlagh Hadi Moradi Hamidreza Pouretemad Advanced Robotics and Intelligent Systems Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran ARIS and CIPCE School of ECE College of Engineering University of Tehran Iran Shahid Beheshti University Tehran Tehran IR

ISBN: (纸本)9781467357661

Early detection of autism is crucial for successfully dealing with it and reduce/eliminate its effects. In other words, early treatment can make a big difference in the lives of many children with this disorder. Consequently, in this study the pattern recognition algorithms are used to determine the unique features of the voice of autistic children to distinguish between the autistic children and normal children between ages 2 and 3. These descriptors extract various audio features such as temporal features, energy features, harmonic features, perceptual and spectral features. Two feature selection methods are used and the results are compared. One method is based on comparing the effect of using all of a group features together and another method compares the effect of using features one by one. The selected features are used to classify selected children into autistic and non-autistic ones. The results show 96.17 percent accuracy. After feature selection, we classified data using S.V.M classifier for recognizing two types of input data.

关键词： Autism Feature extraction Mel frequency cepstral coefficient Educational institutions Harmonic analysis Accuracy Motion pictures

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