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Iranian Conference of Biomedical Engineering (ICBME)

作者： Farzaneh Keivanfard Mohammad Teshnehlab Mahdi Aliyari Shoorehdeli Ke Nie Min-Ying Su Electrical and Computer Engineering Department Khaje Nasir Toosi University of Technology Tehran Iran Electrical and Computer Engineering Department Advanced Process Automation and Control (APAC) Khaje Nasir Toosi University of Technology Tehran Iran Center for Functional Onco-Imaging and Department of Radiological Sciences University of California Irvine CA USA

In this paper, a new feature selection and classification methods based on artificial neural network are applied to classify breast cancer on dynamic Magnetic Resonance Imaging (MRI). The database including benign and malignant lesions is specified to select the features and classify with proposed methods. It is collected from 2004 to 2006. A forward selection method is applied to find the best features for classification. Moreover, artificial neural networks such as Multilayer Preceptron (MLP) neural network, Probabilistic Neural Network (PNN) and Generalized Regression Neural Network (GRNN) are applied to classify breast cancer into two groups; benign and malignant lesions. Training and recalling neural networks are obtained with considering four-fold cross validation.

关键词： Fires Entropy Correlation Artificial neural networks Lesions Jacobian matrices Kinetic theory

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Sensor data fusion using fuzzy control for VOR-based vision tracking system

Sensor data fusion using fuzzy control for VOR-based vision ...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Hyun-il Kwon Jaehong Park Wonsang Hwang Jong-hyeon Kim Chang-hun Lee M. Latif Anjum Kwang-soo Kim Dong-il Cho Automation and Systems Research Institute and School of Electrical Engineering and Computer Science Inter-University Semiconductor Research Center Seoul South Korea Department of Control and Instrumentation Engineering Hanbat National University Daejeon South Korea

This paper presents a vision tracking system to achieve high recognition performance under dynamic circumstances, using a fuzzy logic controller. The main concept of the proposed system is based on the vestibulo-ocular reflex (VOR) and the opto-kinetic reflex (OKR) of the human eye. To realize the VOR concept, MEMS inertial sensors and encoders are used for robot motion detection. This concept turns the camera towards a selected target, counteracting the robot motion. Based on the OKR concept, the targeting errors are periodically compensated, using vision information. The fuzzy logic controller uses sensor data fusion to detect slip or collision occurrences. To calculate a heading angle of the camera accurately, the output of the fuzzy logic controller and the vision information from the camera are combined, using an extended Kalman filter. The proposed vision tracking system is implemented in a mobile robot and evaluated experimentally. The experimental results are obtained as the tracking and the recognition success rate using a mobile robot. The developed system achieved the excellent tracking and recognition performance during slip or collision occurrences under dynamic circumstances.

关键词： Cameras Mobile robots Robot vision systems Machine vision Fuzzy logic

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High performance vision tracking system for mobile robot using sensor data fusion with Kalman filter

High performance vision tracking system for mobile robot usi...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Jaehong Park Wonsang Hwang Hyun-il Kwon Jong-hyeon Kim Chang-hun Lee M. Latif Anjum Kwang-soo Kim Dong-il Cho Automation and Systems Research Institute (ASRI) and School of Electrical Engineering and Computer Science Inter-University Semiconductor Research Center Seoul South Korea South Korea Department of Control and Instrumentation Engineering Hanbat National University Daejeon South Korea

This paper introduces a high performance vision tracking system for mobile robot using sensor data fusion. For mobile robots, it is difficult to collect continuous vision information due to robot's motion. To solve this problem, the proposed vision tracking system estimates the robot's position relative to a target and rotates the camera towards the target. This concept is derived from the human eye reflex mechanism, known as the Vestibulo-Ocular Reflex (VOR), for compensating the head motion. This concept for tracking the target results in much higher performance levels, when compared with the conventional method that rotates the camera using only vision information. The proposed system do not require heavy computing loads to process image data and can track the target continuously even during vision occlusion. The robot motion information is estimated using data from accelerometer, gyroscope, and encoders. This multi-sensor data fusion is achieved using Kalman filter. The proposed vision tracking system is implemented on a two-wheeled robot. The experimental results show that the proposed system achieves excellent tracking and recognition performance in various motion scenarios, including scenarios where camera is temporarily blocked from the target.

关键词： Robot sensing systems Target tracking Machine vision Kalman filters Cameras

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Optimal trajectory generation for dynamic street scenarios in a Frenét Frame

Optimal trajectory generation for dynamic street scenarios i...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Moritz Werling Julius Ziegler Sören Kammel Sebastian Thrun Department of Applied Computer Science and Automation (AIA) University of Karlsruhe Karlsruhe Germany Department of Measurement and Control (MRT) University of Karlsruhe Germany Research and Technology Center Robert Bosch Limited Liability Company Palo Alto CA USA Stanford Artificial Intelligence Laboratory University of Stanford Stanford CA USA

Safe handling of dynamic highway and inner city scenarios with autonomous vehicles involves the problem of generating traffic-adapted trajectories. In order to account for the practical requirements of the holistic autonomous system, we propose a semi-reactive trajectory generation method, which can be tightly integrated into the behavioral layer. The method realizes long-term objectives such as velocity keeping, merging, following, stopping, in combination with a reactive collision avoidance by means of optimal-control strategies within the Frenét-Frame of the street. The capabilities of this approach are demonstrated in the simulation of a typical high-speed highway scenario.

关键词： Trajectory Vehicle dynamics Remotely operated vehicles Aerodynamics Road vehicles Mobile robots Merging Road transportation Traffic control Robotics and automation

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A New Strategy of Preparing Multiwall Carbon Nanotube/PC/ABS Nanocomposite by a Reactive Compatibilizer

A New Strategy of Preparing Multiwall Carbon Nanotube/PC/ABS...

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第七届亚澳复合材料会议

作者： Lung-Chien Wu Hsu-Chiang Kuan Shih-Liang Huang Mei-Huei Tsai Min-Chi Chung Chia-Hsun Chen Department of Chemical and Materials Engineering National Chin-Yi University of Technology411Taichung countyTaiwan Department of Computer Application EngineeringFar East University 744Tainan countyTaiwan Department of Automation and Control EngineeringFar East University 744Tainan countyTaiwan Department of Materials Science and EngineeringFar East University 744Tainan countyTaiwan

A novel multiwall carbon nanotube(MWNT) / PC/ABS nanocomposite was prepared in this *** modifier, vinyl trimethoxy silane (VTMOS) and maleic anhydride (MA), were grafted to the MWNT surface via the free radical reaction.A reactive compatibilizer, styrene maleic anhydride(SMA), was employed to produce the chemical bonding between PC/ABS and the modified *** physical properties of these carbon nanotube / PC/ABS resin nanocomposite was studied.

关键词： Compatibilizer Functionalize Carbon nanotubes PC/ABS

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Comparison between two FPGA implementations of the Particle Swarm Optimization algorithm for high-performance embedded applications

Comparison between two FPGA implementations of the Particle ...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Daniel M. Muñoz Carlos H. Llanos Leandro dos S. Coelho Mauricio Ayala-Rincón Department of Mechanical Engineering GRACO University of Brasilia Brasilia D.F. Brazil Department of Mechanical Engineering Automation and Control Group/GRACo University of Brasilia Brasilia Brazil Industrial and Systems Engineering LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. There are several embedded applications which requires to solve online optimization problems with a high performance. However, the PSO suffers on large execution times, and this fact becomes evident when using Reduced Instruction Set computer (RISC) microprocessors in which the operational frequencies are low in comparison with the high operational frequencies of traditional personal computers (PCs). This paper compares two hardware implementations of the parallel PSO algorithm using an efficient floating-point arithmetic which perform computations with large dynamic range and high precision. The full-parallel and the partially-parallel PSO architectures allow the parallel capabilities of the PSO to be exploited in order to decrease the running time. Three well-known benchmark test functions have been used to validate the hardware architectures and a comparison in terms of cost in logic area, quality of the solution and performance is reported. In addition, a comparison of the execution time between the hardware and two C-code software implementations, based on a Intel Core Duo at 1.6GHz and a embedded Microblaze microprocessor at 50MHz, are presented.

关键词： Mathematics Hardware

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Delay-dependent conditions for monotonic convergence of uncertain ILC systems: An LMI approach

Delay-dependent conditions for monotonic convergence of unce...

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IEEE Conference on Decision and control

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division the Department of Systems and Control Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

ISBN: (纸本)9781424477456

This paper deals with the iterative learning control (ILC) problem for uncertain time-delay systems (TDS). In order to ensure monotonic convergence of the ILC process, a sufficient condition is developed using an H ∞ -based framework. It shows that under this framework, the convergence condition is enabled to be delay-dependent and have a formulation in terms of linear matrix inequalities (LMIs). Moreover, formulas for the updating law design can be derived by directly solving LMIs. A numerical example is provided to verify that the delay-dependent condition in LMI forms is effective in producing monotonically convergent ILC algorithms.

关键词： Convergence Symmetric matrices Robustness Delay Uncertainty Performance analysis Linear matrix inequalities

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Local Stability Analysis of Feedback Linearizing Schemes for a Class of Uncertain Nonlinear Systems *

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IFAC Proceedings Volumes 2010年第14期43卷 1394-1399页

作者： E.R. Rohr L.F.A. Pereira D.F. Coutinho School of Electrical Engineering and Computer Science University of Newcastle University Drive Callaghan NSW 2308 Australia Electrical Engineering Department Universidade Federal do Rio Grande do Sul Av. Osvaldo Aranha 103 Porto Alegre - RS - Brazil Group of Automation and Control Systems PUCRS Av. Ipiranga 6681 90619-900 Porto Alegre Brazil

This work presents a (numerical) technique to the local stability analysis of feedback linearizing control schemes for a class of uncertain nonlinear systems. A nonlinear decomposition of vector functions is applied to transform the Lyapunov stability conditions into a set of state-and parameter-dependent LMI (linear matrix inequality) constraints, which are numerically solved in a finite set of points. The proposed method can deal with a large class of nonlinear systems as well as very complex Lyapunov function candidates. In addition, a maximized level set of the Lyapunov function is proposed as an estimate of the system stability region.

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New enhancement of infrared image based on human visual system

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Chinese Optics Letters 2009年第3期7卷 206-209页

作者：于天河李秋明戴景民 Department of Automation Measurement and Control Engineering Harbin Institute of Technology Computer Center Harbin University of Science and Technology School of Astronautics Harbin Institute of Technology

Infrared images are firstly analyzed using the multifractal theory so that the singularity of each pixel can be extracted from the images. The multifractal spectrum is then estimated, which can reflect overall characteristic of an infrared image. Thus the edge and texture of an infrared image can be accurately extracted based on the singularity of each pixel and the multifractal spectrum. Finally the edge pixels are classified and enhanced in accordance with the sensitivity of human visual system to the edge profile of an infrared image. The experimental results obtained by this approach are compared with those obtained by other methods. It is found that the proposed approach can be used to highlight the edge area of an infrared image to make an infrared image more suitable for observation by human eyes.

关键词： Imaging systems Infrared imaging Infrared spectroscopy Pixels

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Model Matching control for MIMO Systems with Multiple Time Delays and Its Applications in Adaptive Scheme

Model Matching Control for MIMO Systems with Multiple Time D...

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American control Conference

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu 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 Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper considers the model matching problem of multiple-input multiple-output (MIMO) systems with multiple time delays. The reference model is chosen to be the diagonal delay transfer function matrix. A controller is designed for nominal systems. Furthermore, an adaptive control scheme is proposed for uncertain systems with parameter variation. The resulting scheme can guarantee the global stability of the closed-loop systems and the convergence of the tracking errors. A simulation example is included to illustrate the proposed scheme.

关键词： control system synthesis MIMO Delay effects Programmable control Adaptive control Transfer functions control systems Uncertain systems Stability Convergence

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