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A New Discrete-time Adaptive ILC for Nonlinear systems with Time-varying Parametric Uncertainties

自动化学报 2008年第7期34卷 805-808页

作者： CHI Rong-Hu SUI Shu-Lin HOU Zhong-Sheng Institute of Autonomous Navigation and Intelligent Control School of Automation and Electrical Engineering Qingdao University of Science and Technology Qingdao 266042 P.R. China Advanced Control Systems Laboratory School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 P. R. China

用在分离时间轴和反复的学习轴之间的类比，一条新分离时间的适应反复的学习控制(AILC ) 途径被开发与变化时间的参量的无常探讨非线性的系统的一个班。类似于适应控制，新 AILC 能合并一个设计算法，因此，学习获得能沿着学习的轴反复... 详细信息

用在分离时间轴和反复的学习轴之间的类比，一条新分离时间的适应反复的学习控制(AILC ) 途径被开发与变化时间的参量的无常探讨非线性的系统的一个班。类似于适应控制，新 AILC 能合并一个设计算法，因此，学习获得能沿着学习的轴反复地被调节。当起始的状态是随机的，参考轨道是变化重复的时，新 AILC 能沿着反复的学习轴 asymptotically 在有限时间间隔上完成 pointwise 集中。

关键词：自动化技术智能系统非线性系统离散时间系统不确定性

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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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Navigation of an omni-directional mobile robot with active caster wheels

Navigation of an omni-directional mobile robot with active c...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Eui-jung Jung Ho Yul Lee Jae Hoon Lee Byung-Ju Yi Whee Kuk Kim Shin'ichi Yuta School of Electrical Engineering and Computer Science Hanyang University South Korea Intelligent Systems Research Institute Ubiquitous Functions Research Group AIST Japan Department of Control and Instrumentation Engineering Korea University South Korea Institute of Engineering Mechanics and Systems University of Tsukuba Japan

This work deals with navigation of an omni-directional mobile robot with active caster wheels. Initially, the posture of the omni-directional mobile robot is calculated by using the odometry information. Next, the position accuracy of the mobile robot is measured through comparison of the odometry information and the external sensor measurement. Finally, for successful navigation of the mobile robot, a motion planning algorithm that employs kinematic redundancy resolution method is proposed. Through experiments for multiple obstacles and multiple moving obstacles, the feasibility of the proposed navigation algorithm was verified.

关键词： Navigation Mobile robots Wheels Kinematics computer science Position measurement Roads Robotics and automation USA Councils Motion planning

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An Application of Convex Optimization Concepts to Approximate Dynamic Programming

An Application of Convex Optimization Concepts to Approximat...

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2008 American control Conference (ACC), vol.10

作者： Edilson F. Arruda Marcelo D. Fragoso Joao Bosco R. do Val Department of Systems And Control National Laboratory for Scientific Computing Petropolis Rio de Janeiro Brazil Department of Telematics School of Electrical and Computer Engineering State University of Campinas Sao Paulo Brazil

This paper deals with approximate value iteration (AVI) algorithms applied to discounted dynamic (DP) programming problems. The so-called Bellman residual is shown to be convex in the Banach space of candidate solutions to the DP problem. This fact motivates the introduction of an AVI algorithm with local search that seeks an approximate solution in a lower dimensional space called approximation architecture. The optimality of a point in the approximation architecture is characterized by means of convex optimization concepts and necessary and sufficient conditions to global optimality are derived. To illustrate the method, two examples are presented which were previously explored in the literature.

关键词： Dynamic programming Function approximation Approximation algorithms Sufficient conditions Stochastic processes Large-scale systems Heuristic algorithms Robustness Convergence computer architecture

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Nonlinear Modelling and control of an Autonomous Underwater Vehicle

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IFAC Proceedings Volumes 2008年第1期41卷 1-6页

作者： Wasif Naeem Robert Sutton Intelligent Systems and Control Group School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast BT9 5AH UK (Tel: 44 2890 974066) Marine and Industrial Dynamic Analysis Research Group School of Engineering The University of Plymouth Plymouth PL4 8AA UK

This paper highlights nonlinear modelling and control of the Hammerhead AUV. To model the AUV, a multi-layer perceptron neural network structure has been chosen. Data from actual trials is utilised for training and validating the neural network model. A genetic algorithm (GA) based nonlinear model predictive control (MPC) algorithm is also implemented to the identified model and results are shown for two waypoint following scenarios involving step changes in reference heading. It is demonstrated that the neural network is able to model the system well and the GA-based nonlinear MPC autopilot is quite capable of dealing with nonlinear nonconventional models.

关键词： Modelling neural networks model predictive control genetic algorithms autonomous underwater vehicles

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Result representation of Rao-Blackwellized particle filtering for SLAM

Result representation of Rao-Blackwellized particle filterin...

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International Conference on control, Automation and systems ( ICCAS)

作者： Nosan Kwak Beom-Hee Lee Kazuhito Yokoi Joint Japanese-French Robotics Laboratory Intelligent Systems Research Institute National Institute for Advanced Industrial Science and Technology Tsukuba Japan School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea

Recently, particle filters have been applying to many robotic problems including the simultaneous localization and mapping (SLAM). Specifically, SLAM approaches employing Rao-Blackwellized particle filter (RBPF) have shown good results. However, no research is conducted to analyze representation of the results of particle filtering. After finishing the particle filtering, the results such as a map and a path are stored in the separate particles. In most cases, the result of the particle that has the highest importance weight is represented as the result. However, this approach does not give the best result all the time. Thus, We provide the analysis of final representation of particle filtering. In this paper, we compares several methods to derive the final representation of the result after finishing RBPF-SLAM. According to the result, combining data of each particle provides the better result with high probability than using just data of a particle such as the highest weighted particle representation.

关键词： Filtering Simultaneous localization and mapping Particle filters intelligent robots Robotics and automation Service robots Electronic mail Finishing Diversity reception Automatic control

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Reduced Reference Watermark-Based Image Transmission Quality Metric

Reduced Reference Watermark-Based Image Transmission Quality...

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3rd International Symposium on Communications, control, and Signal Processing (ISCCSP 2008), vol.1

作者： Mohammad Hosain Kayvanrad Shabnam Sodagari Alireza Nasiri Avanaki Hossein Ahmadi-Noubari Embedded Video (EV) Laboratory Department of ECE National University of Singapore Singapore Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Iran Department of ECE University of British Columbia University of Tehran Iran

A novel reduced reference (RR) method of channel estimation for image transmission through lossy channels is presented. Estimation is based on the amount of distortion the low frequency content of the image or its histogram suffers during transmission. This distortion is computed by sending the low frequency content of the original image or the corresponding histogram to the receiver by means of a robust watermark. Simulations for different types of images and different channel losses yield large amounts of correlation between the estimated Mean Square Error (MSE) and the structural similarity (SSIM) index.

关键词： Image transmission Reduced reference quality assessment Watermarking Two dimensional wavelet transform Histogram

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

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International Conference on Information Fusion

作者： Nima Tajbakhsh Babak N. Araabi Hamid Soltanianzadeh Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Iris Feature extraction Discrete cosine transforms Image recognition Databases Training Humans

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Output feedback control of linear systems with input and output quantization

Output feedback control of linear systems with input and out...

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IEEE Conference on Decision and control

作者： Daniel Coutinho Minyue Fu Carlos E. de Souza Group of Automation and Control Systems Faculty of Engineering Pontifícia Universidade Católica do Rio Grande do Sul Porto Alegre Brazil School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW Australia Department of Systems and Control Laboratory Nacional de Computação Científica Petropolis Rio de Janeiro Brazil

ISBN: (纸本)9781424431236

A considerable amount of research has been done on the use of logarithmic quantizers for networked feedback control systems. However, most results are developed for the case of a single quantizer (either measurement or control signal quantization). In this paper, we investigate the case of simultaneous input and output quantization for SISO linear output feedback systems. Firstly, we show that the problem of quadratic stabilization via quantized feedback can be addressed with no conservativeness by means of the sector bound approach. Secondly, we provide a bound on the maximal admissible sector bound via a scaled H ¿ optimization problem.

关键词： Output feedback Linear feedback control systems control systems Linear systems Quantization Communication system control Feedback control Communication channels Digital control Bandwidth

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Constrained optimization of nonparametric entropy-based segmentation of brain structures

Constrained optimization of nonparametric entropy-based segm...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi Asl Hamid Soltanian-Zadeh School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

We propose a constrained, three-dimensional, nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capture structural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function, which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, constraints are used to improve segmentation quality. These constraints are extracted from training data. Sample results are given for the segmentation of caudate, hippocampus, and putamen, illustrating highly superior performance of the proposed method compared to the most similar methods in the literature.

关键词： Constraint optimization Brain Iterative algorithms Image segmentation Shape Couplings Magnetic resonance Magnetic resonance imaging Principal component analysis Buildings

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