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Flexible triangular formation keeping of marine robotic vehicles using range measurements 1

IFAC Proceedings Volumes 2014年第3期47卷 5145-5150页

作者： Francisco Rego Jorge M. Soares António Pascoal A. Pedro Aguiar Colin Jones Laboratory of Robotics and Systems in Engineering and Science Instituto Superior Técnico University of Lisbon Lisbon Portugal Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Porto Portugal Institute of Mechanical Engineering School of Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland National Institute of Oceanography Dona Paula Goa India

This paper addresses the problem of keeping an autonomous marine vehicle in a moving triangular formation by regulating its position with respect to two leader vehicles. The follower vehicle has no prior knowledge of the path described by the leaders but has access to their heading angle and is able to measure inter-vehicle ranges. It is assumed that the distance between the leaders is constant and known. A control strategy is adopted that generates speed and heading commands so as to drive suitably defined along track and cross track errors to zero. The commands are used as input to local inner loops for yaw and speed control. The paper describes the algorithms derived for range-based control and assesses their performance in simulations using realistic models of the vehicles involved. Tests with three autonomous marine vehicles equipped with acoustic modems and ranging devices allow for the evaluation of the performance of the algorithms in a real-world situation.

关键词： Autonomous Vehicles Marine Systems Control Laws Formation Control Station Keeping Triangular Formations

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A Cloaking-Based Approach to Protect Location Privacy in Location-Based Services

A Cloaking-Based Approach to Protect Location Privacy in Loc...

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第三十三届中国控制会议

作者： Zheng Jiangyu Tan Xiaobin Cliff Zou Niu Yukun Zhu Jin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Department of Automation University of Science and Technology of China Department of Electrical Engineering and Computer Science University of Central FloridaOrlandoFL 32816-2362

ISBN: (纸本)9781479947249

With the widespread use of mobile devices, the location-based service(LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a user expects to report his own location as far as possible away from his real location to protect his location privacy. On the other hand, in order to obtain high quality of service(QoS), users are required to report their locations as accurate as possible. To achieve the dedicated tradeoff between privacy requirement and QoS requirement, we propose a novel approach based on cloaking technique. We also discuss the disadvantage of the traditional general system model and propose an improved model. The basic idea of our approach is to select a sub-area from the generated cloaking area as user's reported location. The sub-area may not contain a user's real location,which prevents an adversary from performing attack with side information. Specifically, by defining an objective function with a novel location privacy metric and a QoS metric, we are able to convert the privacy issue to an optimization problem. Then, location privacy metric and QoS metric are given. To reduce the complexity of the optimization, a heuristic algorithm is *** privacy-preserving analysis and comparison with related work [8], we demonstrate the effectiveness and efficiency of our approach.

关键词： Location-based Services,Location Privacy,k-anonymity,Cloaking Area

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An efficient two-stage gene selection method for microarray data

Communications in Computer and Information Science

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Communications in computer and Information Science 2013年 355卷 424-432页

作者： Du, Dajun Li, Kang Deng, Jing Key Laboratory of Power Station Automation Technology Department of Automation Shanghai University 200072 Shanghai China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom

Gene selection is a key issue in the analysis of microarray data with small samples and variant correlation. The main objective of this paper is to select the most informative genes from thousands of genes with strong correlation. This is achieved by proposing an efficient two-stage gene selection (TSGS) algorithm. In this algorithm, the L2- norm penalty are firstly introduced to achieve the grouping effect for the highly correlated genes. To overcome the small samples problem, the augmented data technique is then used to produce an augmented data set. Finally, by using the recently proposed two-stage algorithm, the most informative genes can be selected effectively. Simulation results confirm its effectiveness of the proposed approach in comparison with the popular Elastic Net method. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Genes

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Program-based and model-based PLC design environment for multicore FPGA architectures

Program-based and model-based PLC design environment for mul...

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International Conference on Informatics in Control, automation and robotics (ICINCO)

作者： Christoforos Economakos Michael Skarpetis George Economakos Technological Educational Institution of Sterea Ellada Department of Automation Engineering GR34400 Psahna Evia Greece National Technical University of Athens School of Electrical and Computer Engineering Microprocessors and Digital Systems Laboratory Heroon Polytechniou 9 GR15780 Zografou Greece

Digital design has been growing rapidly during the last years, offering advanced implementation solutions for a diversity of appliances and instruments, integrating different sensors and actuators. This has a great impact on embedded automation, where traditional Programmable Logic Controllers (PLCs) have been gradually replaced by high performance Embedded Controllers, Digital Signal Processor (DSP) chips and, more recently, power efficient Field Programmable Gate Arrays (FPGAs). Such new implementation platforms bring together efficient design methodologies, like model-based design and high-level or C level program-based design. In their turn, new design methodologies are accompanied by new design technologies like Intellectual Property (IP) based design and High-Level Synthesis (HLS). This paper presents a design environment that utilizes program-based and model-based design, for the development of PLC applications. Specifically, a tool flow is constructed that supports either the design of new control algorithms or the translation of existing algorithms into C. Then, HLS and FPGA implementation tools are adopted, to implement the selected algorithms as multicore, embedded designs, offering performance improvements and hardware utilization efficiency. Overall, the proposed methodology and underlying tool flow support a novel high productivity prototyping platform for digital control applications, with very promising future extension capabilities.

关键词： Field programmable gate arrays Algorithm design and analysis Hardware Digital signal processing Signal processing algorithms Microcontrollers Hardware design languages

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Injection-depth-locking axial motion guided handheld micro-injector using CP-SSOCT

Injection-depth-locking axial motion guided handheld micro-i...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Gyeong Woo Cheon Yong Huang Hye Rin Kwag Ki-Young Kim Russell H. Taylor Peter L. Gehlbach Jin U. Kang Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Department of Chemical and Biomolecular Engineering Johns Hopkins University Baltimore MD USA Laboratory of Computational Sensing and Robotics Johns Hopkins University Baltimore MD USA Department of Computer Science Johns Hopkins University Baltimore MD USA Wilmer Eye Institute Johns Hopkins School of Medicine Baltimore MD

This paper presents a handheld micro-injector system using common-path swept source optical coherence tomography (CP-SSOCT) as a distal sensor with highly accurate injection-depth-locking. To achieve real-time, highly precise, and intuitive freehand control, the system used graphics processing unit (GPU) to process the oversampled OCT signal with high throughput and a smart customized motion monitoring control algorithm. A performance evaluation was conducted with 60-insertions and fluorescein dye injection tests to show how accurately the system can guide the needle and lock to the target depth. The evaluation tests show our system can guide the injection needle into the desired depth with 4.12μm average deviation error while injecting 50nl of fluorescein dye.

关键词： Needles Optical fiber sensors Biomedical optical imaging Optical fibers Optical interferometry Coherence

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Social Adaptation of Robots for Modulating Self-Organization in Animal Societies

Social Adaptation of Robots for Modulating Self-Organization...

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IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW

作者： Payam Zahadat Michael Bodi Ziad Salem Frank Bonnet Marcelo Elias De Oliveira Francesco Mondada Karlo Griparic Tomislav Haus Stjepan Bogdan Rob Mills Pedro Mariano Luis Correia Olga Kernbach Serge Kernbach Thomas Schmickl Artificial Life Laboratory of the Department of Zoology Karl-Franzens University Graz Austria Computer Engineering Department Aleppo University Syrian Arab Republic Rbotic Systems Laboratory Swiss Federal Institute of Technology (EPFL) Lausanne Switzerland Ecole Polytechnique Federale de Lausanne Lausanne VD CH Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Universidade de Lisboa Lisboa Lisboa PT Cybertronica Research Research Center of Advanced Robotics and Environmental Science Stuttgart Germany

The goal of the work presented here is to influence the overall behaviour of specific animal societies by integrating computational mechatronic devices (robots) into those societies. To do so, these devices should be accepted by the animals aspart of the society and/or as part of the collectively formed environment. For that, we have developed two sets of robotic hardware for integrating into societies of two different animals: zebra fish and young honeybees. We also developed mechanisms to provide feedback from the behaviours of societies for the controllers of the robotic system. Two different computational methods are then used as the controllers of the robots in simulation and successfully adapted by evolutionary algorithms to influence the simulated animals for desired behaviours. Together, these advances in mechatronic hardware, feedback mechanisms, and controller methodology are laying essential foundations to facilitate experiments on modulating self-organised behaviour in mixed animal -- robot societies.

关键词： Animals Heating Vibrations Robot sensing systems Hardware Biochemistry

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On Infinite Time Performance of Nonlinear Model Predictive Controllers

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IFAC Proceedings Volumes 2014年第3期47卷 1916-1921页

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 P. R. China School of Electronics Electrical Engineering and Computer Science The Queen's University Belfast Belfast BT7 1NN UK

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

关键词： Model Predictive Control Finite Horizon Optimal Control Value Iteration Principle of Optimality

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Index modulated OFDM with ICI self-cancellation in underwater acoustic communications

Index modulated OFDM with ICI self-cancellation in underwate...

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Asilomar Conference on Signals, Systems & computers

作者： Miaowen Wen Yuke Li Xiang Cheng Liuqing Yang School of Electronic and Information Engineering South China University of Technology Guangzhou China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA

ISBN: (纸本)9781479982981

OFDM is promising for underwater acoustic (UWA) communications due to its potential to combat the large delay spread. However, the performance of the OFDM system is seriously deteriorated by the inter-carrier interference (ICI) caused by the transmitter/receiver motion and ocean waves. In this paper, we propose a novel ICI countermeasure. The key idea is to inactivate partial subcarriers according to index modulation and meanwhile transmit signals with opposite polarity on two adjacent active subcarriers for ICI self cancellation. Simulation results validate that the proposed scheme achieves much better bit error rate (BER) performance than many existing schemes in UWA communications.

关键词： OFDM Modulation Bit error rate Indexes Receivers Transmitters Sonar equipment

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Non Linear Hebbian Learning Techniques and Fuzzy Cognitive Maps in Modeling the Parkinson's Disease

Non Linear Hebbian Learning Techniques and Fuzzy Cognitive M...

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Mediterranean Conference on Control & automation

作者： Anninou P. Antigoni Groumpos P. Peter Laboratory of Automation and Robotics Department of Electrical and Computer Engineering University of Patras

ISBN: (纸本)9781479909964

A new soft computing method using Fuzzy Cognitive Maps for modeling and predicting Parkinson's disease has been proposed. A decision support system based on human knowledge and experience, with a Fuzzy Cognitive Map trained using unsupervised Nonlinear Hebbian Leanring algorithm are proposed. The basic theories of this learning method are reviewed and presented. The initial values of concepts are represented as fuzzy membership values and trained to get new updated weight matrix and new concept values. Simulations are performed and very interesting results are obtained and discussed. A comparison between the results with and without a learning algorithm is considered.

关键词： Fuzzy cognitive maps Parkinson Disease decision support systems Hebbian principle Learning methods learning algorithms Modeling

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Enhancing the Effectiveness of Fungicides by Optimizing Their Combinations

Enhancing the Effectiveness of Fungicides by Optimizing Thei...

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第26届中国控制与决策会议

作者： Xiang Wang Jia Ma Xiaowei Li Xiaodong Zhao Zongli Lin Jie Chen Zhifeng Shao Department of Automation and Key Laboratory of System Control and Information Processing of the Ministry of EducationShanghai Jiao Tong University Department of Resource and Environmental Science School of Agriculture and BiologyShanghai Jiao Tong University School of Biomedical Engineering Shanghai Jiao Tong University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

In controlling biological diseases, it is often more potent to use a combination of agents than using individual ones. However, the number of possible combinations increases exponentially with the number of agents and their concentrations. It is prohibitive to search for effective agent combinations by trial and error as biological systems are complex and their responses to agents are often a slow process. This motivates to build a suitable model to describe the biological systems and help reduce the number of experiments. In this paper, we consider the use of fungicides to inhibit Bipolarismaydis and construct models that describe the responses to fungicide combinations. Three data-driven modeling methods, the polynomial regression, the artificial neural network and the support vector regression, are compared based on the experimental data of the inhibition rates of the southern corn leaf blight with different fungicide combinations. The analysis of the results demonstrates that the support vector regression is best suited to the construction of the response model in terms of achieving better prediction with fewer experiments.

关键词： agent combinations,complex system,data-driven model,polynomial regression,artificial neural network,support vector regression

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