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2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016

作者： Meiling, Wang Zhen, Wang Yi, Yang Mengyin, Fu Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781509041022

In this paper, a simplified dynamic vehicle model is established to accurately describe the dynamics of Unmanned Ground Vehicle (UGV) in trajectory tracking, while meeting the real-Time computing requirement. And a modified model predictive control (MPC) algorithm with soft constraint for UGV trajectory tracking is proposed to improve the tracking stability and rapidity. The optimal control problem at each sampling time is converted into a quadratic program (QP), which has mature solutions. To verify the trajectory tracking capabilities, the proposed MPC controller is compared with a PD controller under different longitudinal velocities. The simulation results demonstrate that the MPC controller can effectively reduce the tracking error and ensure the vehicle's traveling smoothness. © 2016 IEEE.

关键词： Model predictive control

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An online state and parameter estimation of dynamic state space model of high speed train

International Journal of Control and Automation

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International Journal of Control and Automation 2016年第9期9卷 51-62页

作者： Xie, Guo Zhang, Dan Hei, Xinhong Qian, Fucai Takahashi, Sei Nakamura, Hideo Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an Shaanxi710048 China College of Science and Technology Nihon University 7-24-1 Narashinodai Funabashi Chiba274-8501 Japan

In this paper, the state space model of high speed train is established to describe its nonlinear dynamic characteristics, whose parameters are disturbed by noise with an arbitrary distribution, and an online state and parameter identification method is proposed based on a parameters set by employing Bayesian theory and Particle Filter (PF). Firstly, the priori probabilities of all of the possible parameters are set to be equal, and the predicted states with different parameters are estimated using PF. Then the posterior probabilities of the parameters are updated by analyzing the characteristic of the measurement noise using Bayesian theory. Finally, the system sate and parameter are estimated by weighted summing all of the parameters and predicted states. The simulation results indicate that the proposed method can estimate the states and parameters of high speed train online and adaptively. © 2016 SERSC.

关键词： State space methods

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Analysis of underwater locomotion and improvement of FroBot

Analysis of underwater locomotion and improvement of FroBot

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2016 IEEE International Conference on Advanced intelligent Mechatronics, AIM 2016

作者： Yi, Yang Jianqing, Zhang Han, Xu Maokuan, Chen Lu, Zhang Zhongjing, Zhu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Electronic Engineering School of Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781509020652

The main characteristic of FroBot is the dual-swing-legs propulsion mechanism, and it is necessary for us to conduct a series of experiments to study its propulsion model, both on land and underwater. As the propulsion of FroBot comes from the interaction force between caudal fins and water when it locomotes underwater, this paper presents an analysis about the propulsion and control of angle Θ. Then a number of underwater hydrodynamic simulations and analysis are also conducted to get a better control in reality. Finally, on the basis of propulsion model and experiments, we present the latest mechanical structure designs and further improvements to eliminate the limitations exposed in the previous generations of FroBot. © 2016 IEEE.

关键词： Propulsion

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Riddling: Chimera's dilemma

arXiv

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arXiv 2018年

作者： Santos, V. Szezech, J.D. Batista, A.M. Iarosz, K.C. Baptista, M.S. Ren, H.P. Grebogi, C. Viana, R.L. Caldas, I.L. Maistrenko, Y.L. Kurths, J. Graduate in Science Program State University of Ponta Grossa Ponta Grossa Paraná84030-900 Brazil Department of Mathematics and Statistics State University of Ponta Grossa Ponta Grossa Paraná84030-900 Brazil Potsdam Institute for Climate Impact Research Potsdam Brandenburg14473 Germany Institute of Physics University of São Paulo São Paulo05508-900 Brazil Department of Physics Humboldt University Berlin Brandenburg12489 Germany Institute for Complex Systems and Mathematical Biology SUPA University of Aberdeen Aberdeen ScotlandAB24 3UE United Kingdom Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Department of Physics Federal University of Paraná Curitiba Paraná80060-000 Brazil Institute of Mathematics Centre for Medical and Biotechnical Research National Academy of Sciences of Ukraine Tereshchenkivska St. 3 Kyiv01030 Ukraine

We investigate the basin of attraction properties and its boundaries for chimera states in a circulant network of Hénon maps. It is known that coexisting basins of attraction lead to a hysteretic behaviour in the diagrams of the density of states as a function of a varying parameter. Chimera states, for which coherent and incoherent domains occur simultaneously, emerge as a consequence of the coexistence of basin of attractions for each state. Consequently, the distribution of chimera states can remain invariant by a parameter change, as well as it can suffer subtle changes when one of the basins ceases to exist. A similar phenomenon is observed when perturbations are applied in the initial conditions. By means of the uncertainty exponent, we characterise the basin boundaries between the coherent and chimera states, and between the incoherent and chimera states, respectively. This way, we show that the density of chimera states can be not only moderately sensitive but also highly sensitive to initial conditions. This chimera's dilemma is a consequence of the fractal and riddled nature of the basins boundaries. Coupled dynamical systems have been used to describe the behaviour of real complex systems, such as power grids, neuronal networks, economics, and chemical reactions. Furthermore, these systems can exhibit various kinds of interesting nonlinear dynamics, e.g. synchronisation, chaotic oscillations, and chimera states. The chimera state is a spatio-temporal pattern characterised by the coexistence of coherent and incoherent dynamics. It has been observed in a great variety of systems, ranging from theoretical and experimental arrays of oscillators, to in phenomena such as the unihemispheric sleep of cetaceans. We study the chimera state in a circulant network of Hénon maps, seeking to determine how the density of states in the network depends on the system parameters and the initial conditions. We have found that, as expected, the density of states might be inva

关键词： Neurons

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Autonomous landing of a quadrotor on an UGV

Autonomous landing of a quadrotor on an UGV

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IEEE International Conference on Mechatronics and Automation

作者： Mengyin Fu Kuan Zhang Yang Yi Chao Shi Nanjing University of Science and Technology Nanjing China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509023974

This paper provides a complete solution for landing a quadrotor Unmanned Aerial Vehicle (UAV) on an Unmanned Ground Vehicle (UGV) in the outdoor environment. An image-based visual servo control law and a GPS-based navigation method are proposed, and the former method acquires the visual feedback from the camera attached to the quadrotor, while the latter strategy is used when the visual feedback is absent. For achieving more precise and stable performance in visually guided landing process, we design a specific landing marker that can provide different features as the distance between the quadrotor and landing target changes. Meanwhile, the corresponding detection and recognition algorithms are raised. Finally, a simulation experiment is carried out to validate the proposed vision algorithms and control strategies.

关键词： Visualization Cameras Unmanned aerial vehicles Mathematical model Land vehicles Navigation Servosystems

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Filling Modules into Spaces for Rapid Prototyping of Mechanical Assembly: Algorithm

Filling Modules into Spaces for Rapid Prototyping of Mechani...

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IEEE Conference on Industrial Electronics and Applications

作者： Z. Q. Qian B. Han Y. Lin W. J. Lin W. J. Zhang Complex and Intelligent System Research Center East China University of Science and Technology Department of Mechanical and Industrial Engineering Northeastern University Advanced Engineering Design Laboratory University of Saskatchewan

ISBN: (纸本)9781467386456

This paper proposes a computational model along with an algorithm for a new problem in computer-aided design of systems. The new problem stems from a so-called rapid prototyping of system (RPS) technology the authors developed elsewhere before. The RPS has learned from traditional rapid prototyping technique which is in essence to construct a component from the material (liquid, sheet, etc.);but the RPS is to build a system from modules or components. In the RPS technology, a space is divided into several regions that represent different components. For the visualization purpose, one can imagine that different regions are painted in different colors. Further, modules have different types. The core issue with the RPS is to "fill" modules of different types to a colored space. This problem is called the RPS problem for simplicity. The proposed model is an optimization problem model and algorithm is a combination of the differential evolution and genetic algorithm. The proposed model along with the algorithm is tested and compared with other algorithms on three examples. The result of the comparisons has shown that the proposed model along with the algorithm can well solve this RPS problem.

关键词： Rapid prototyping of systems Modular module Genetic algorithm Differential evolution

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Transfer function of fluidic system in liquid-circular angular accelerometer

Transfer function of fluidic system in liquid-circular angul...

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IEEE Instrumentation and Measurement Technology Conference

作者： Siyuan Cheng Meiling Wang Xiang Li Meifeng Xiao Mengyin Fu Xin Zheng Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing China Nanjing University of Science and Technology Nanjing China The Third Academic of Aerospace and Technology Group of China Beijing China

ISBN: (纸本)9781467392211

In this paper, a new kind of liquid-circular angular accelerometer is studied. Based on electrokinetic phenomenon, this angular accelerometer is designed with a porous transducer and fluid mass. Due to the existence of electrical double layer between transducer and fluid mass, this angular accelerometer is able to convert angular acceleration input to electrical signal. The whole system is composed of fluidic system and molecular electronic system. Theoretical analysis and several experiments are implemented to obtain transfer function model of fluidic system. The flow in transducer satisfies the Darcy Law in the experiment and angular velocity input is proved to have no effect on the output. A prototype is designed to compare the output of theoretical model and experiments. All of the experiments prove that the fluidic system of this liquid-circular angular accelerometer can be seen as a first-order system, especially when the frequency of input is less than 30Hz and its transfer function is derived.

关键词： Transducers Fluids Prototypes Accelerometers Transfer functions Electron tubes Acceleration

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Real-time terrain estimation based on multi-scale radial basis function for unmanned ground vehicle

Real-time terrain estimation based on multi-scale radial bas...

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International Conference on Information and Automation (ICIA)

作者： Yi Yang Zhili Wang Xinghe Li Mengyin Fu Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509041039

Accurate terrain estimation is essential for unmanned ground vehicle (UGV) to achieve autonomous navigation. However, some existing approaches are difficult to reconstruct the 3D surface in real-time because of serious amount of computation. A method of environmental terrain estimation based on multi-scale radial basis function with a 3D lidar mounted on a moving vehicle was proposed in this paper. By combining kernel template with terrain grid map, the approach is applicable to the non-uniform density distribution of laser point cloud with the increasing detection range and improves the efficiency of calculation. What's more, the estimation of culverts and trees will be more accurate if treat the point cloud in separate layers for suspended obstacles problem. All terrain estimation approaches were verified with good performance in an interactive system, which is set up with Virtual Robot Experimentation Platform (VREP) and actual vehicle.

关键词： Three-dimensional displays Estimation Laser radar Kernel Lasers Surface reconstruction Real-time systems

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Cooperative output regulation for networked multi-agent systems based on the self-tuning adaptive distributed observer

Cooperative output regulation for networked multi-agent syst...

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American Control Conference

作者： Yi Dong Jie Chen Jie Huang Department of Automation Nanjing University of Science and Technology China The State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology China Department of Mechanical and Automation Engineering the Chinese University of Hong Kong HK

ISBN: (纸本)9781467386838

In this paper, we first propose a self-tuning adaptive distributed observer for a multi-agent system, which is capable of providing the estimation of the leader's signal to various followers without assuming all the followers know the system matrix of the leader and which avoids calculating the observer gain off-line. We then further develop an adaptive distributed control law to solve the cooperative output regulation problem for linear heterogeneous multi-agent systems. This control law offers two advantages in that it makes the least use of the information of the network and the information of the leader system, and it avoids calculating the observer gain.

关键词： Observers Multi-agent systems Communication networks Closed loop systems Nickel Decentralized control Multi-agent systems Closed loop systems decentralised control networks(communications) Output Regulation Observers Nickel Telecommunications control law Self tuning

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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