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检索条件"任意字段=26th International Conference on Methods and Models in Automation and Robotics"

共 1194 条记录，以下是1121-1130 订阅

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A suboptimal control strategy for the start-up of the Open Plate Reactor

A suboptimal control strategy for the start-up of the Open P...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Sener A. Kaya S. A. Attia J. Raisch Electrical Engineering Department Dalarna University Borlange Sweden Control Systems Group Technical University Berlin Berlin Germany

In this paper the application of Nonlinear Model Predictive Control (NMPC) to a chemical reactor, namely the Open Plate Reactor(OPR), is considered. A control strategy which allows a safe start-up operation of the reactor and provides an easy handling of system restrictions and nonlinearities, is proposed. An efficient open-loop parameterization of the control signals is used to further reduce the size of the optimization variables. It is shown that the NMPC algorithm developed gives satisfactory operation and the reduced open loop parameterization results in a sufficiently rich closed loop behavior.

关键词： Inductors Nonlinear control systems Automatic control Predictive models Predictive control Open loop systems Optimization methods Chemical reactors Temperature control robotics and automation

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Investigation of nonlinear orthogonal signal correction algorithm and its effects on multivariate calibration

Investigation of nonlinear orthogonal signal correction algo...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Chunhui Zhao Fuli Wang Zhizhong Mao Jianchang Liu School of Information Science and Engineering Northeastern University Shenyang China

the aim of this paper is to develop a nonlinear orthogonal signal correction (OSC) algorithm using kernel-based technique, termed as kernel OSC (KOSC), and investigate its effects on multivariate calibration. As a nonlinear data pretreatment, the proposed KOSC method can better analyze the nonlinear relationships between descriptor and response variables and remove from process measurement those undesirable variations not correlated with process property from a nonlinear point of view, which well prepares the corrected process trajectory for the subsequent calibration modeling. Two data sets are employed in illustration experiment. It is found that nonlinear OSC plus nonlinear calibration algorithm seems to have the superiority over other methods to improve the interpretation ability of regression model when process data nonlinearly vary with quality.

关键词： Calibration Kernel Algorithm design and analysis robotics and automation Least squares methods Predictive models Industrial relations Failure analysis Information analysis Automatic control

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Scene segmentation based on video structure and spectral methods

Scene segmentation based on video structure and spectral met...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Zhenyuan Zhang Bin Li Hong Lu Xiangyang Xue School of Computer Science Fudan University Shanghai China

Scene is an important semantic unit for video analysis, retrieval and browsing. However, due to the lack of a generic algorithm, many studies focus on specific methods for certain video genes, e.g., news, sports, etc. In this paper, we propose a general framework for scene segmentation. First, we construct a graph, in which the elements encode the shot-to-shot coherent characteristics of a video clip based on visual similarity and temporal relation between shots. In this step, we only exploit the inherent property of video itself and it is independent of video genres. Second, spectral method is applied on the graph to group shots into scenes. the proposed method is not only simple but also effective to deal with organized features. Experimental results validate the robustness of our method on different kinds of videos.

关键词： Layout Hidden Markov models robotics and automation Robustness Automatic control Robot control Robot vision systems Computer science TV Motion detection

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Batch to batch iterative learning control of a fed-batch fermentation process using linearised models

Batch to batch iterative learning control of a fed-batch fer...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Jie Zhang Jerome Nguyan Julian Morris Zhihua Xiong School of Chemical Engineering and Advanced Materials Newcastle University NUT UK Department of Automation Tsinghua University Beijing China

this paper presents an iterative learning control strategy for a fed-batch fermentation process using linearised models identified from process operational data. Off-line calculated control policies for batch fermentation processes may not be optimal when implemented on the processes due to model plant mismatches and/or the presence of unknown disturbances. In order to overcome the effect of model plant mismatches and unknown disturbances, a batch to batch iterative learning control strategy is developed to modify the control actions for the next batch using the information obtained form current and previous batches. the control policy updating is calculated using a model linearised around a reference batch. In order to cope with process variations and disturbances, the reference batch can be taken as the immediate previous batch. After each batch, the newly obtained process operation data is added to the historical process data base and an updated linearised model is re-identified. Since the control actions during different stages of a batch are usually correlated, it is proposed in this paper that the linearised model can be identified from partial least square regression. the proposed technique has been successfully applied to a simulated fed-batch fermentation process.

关键词： Optimal control Neural networks Automatic control robotics and automation Predictive models Industrial control Process control Control systems Recurrent neural networks Least squares methods

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Performances of the likelihood-ratio classifier based on different data modelings

Performances of the likelihood-ratio classifier based on dif...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： C. Chen R.N.J. Veldhuis Signals and Systems Group Electrical Engineeing University of Twente Enschede Netherlands

the classical likelihood ratio classifier easily collapses in many biometric applications especially with independent training-test subjects. the reason lies in the inaccurate estimation of the underlying user-specific feature density. Firstly, the feature density estimation suffers from insufficient number of user-specific samples during the enrollment phase. Even if more enrollment samples are available, it is most likely that they are not reliable enough. Furthermore, it may happen that enrolled samples do not obey the Gaussian density model. therefore, it is crucial to properly estimate the underlying user-specific feature density in the above situations. In this paper, we give an overview of several data modeling methods. Furthermore, we propose a discretized density based data model. Experimental results on FRGC face data set has shown reasonably good performance with our proposed model.

关键词： Covariance matrix Biometrics Independent component analysis Linear discriminant analysis robotics and automation Feature extraction Principal component analysis Bayesian methods Hidden Markov models Support vector machines

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Grey-box modeling of a small-scale helicopter using physical knowledge and Bayesian Techniques

Grey-box modeling of a small-scale helicopter using physical...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Fang Zhou Li Ping Institute of Industrial Process Control University of Zhejiang Hangzhou China

Identification experiments for small-scale helicopters are usually difficult to implement, and the data collected are to some extent non-informative and insufficient. this makes it impossible to identify a parametric model accurate enough for controller design. this paper presents a Bayesian method for identification modeling a small-scale helicopter. Priori physical knowledge is fully applied to simplify the dynamics and obtain two parametric state-space models for both longitudinal and lateral motions. the unknown parameters are explicitly expressed in a more reasonable way. A Bayesian maximum a posteriori (MAP) estimation is formed and translated into a constrained nonlinear optimization problem, which is solved by a Lagrange multiplier method using a DFP-based quasi-Newton recursive algorithm. A ldquosinchrdquo algorithm is applied to map the direct continuous-time domain parameterization problem into the discrete-time domain. the continuous-time state-space model acquired shows good prediction performance and is suitable for controller design.

关键词： Helicopters Bayesian methods Aerodynamics System identification Chirp Testing robotics and automation Parametric statistics Frequency Vehicle dynamics

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Multi features models for robust lip tracking

Multi features models for robust lip tracking

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Quoc Dinh Nguyen Maurice Milgram thi-Hoang-Lan Nguyen Institute of Intelligent Systems and Robotics University of Pierre and Marie Curie-Paris VI Paris France Department of Computer Science Hanoi University of Technology Hanoi Vietnam

We propose and evaluate a novel method for enhancing performance of lips contour tracking, which is based on the concept of statistic shape models (ASM) and multi features. On the first image of the video sequence, lip region is detected using the Bayesian's rule in which lip color information is modeled by using the Gaussian mixture model (GMM) and the GMM is trained by expectation-maximization (EM) algorithm. the lip region is then used to initialize the lip shape model. A single feature-based ASM presents good performance only in particular conditions but gets stuck in local minima for noisy conditions (like beard, wrinkle, poor texture, low contrast between lip and skin, etc). To enhance the convergence, we propose to use 2 features: normal profile and grey level patches, and combine them by using a voting approach. the standard ASM is not able to take into account temporal information from previous frames therefore the lip contours are tracked by replacing the standard ASM with a hybrid active shape model (HASM) which is capable to take advantage of the temporal information. Initial experimental results on video sequences show that MF-HASM is more robust to local minimum problem and gives a higher accuracy than traditional single feature-based method in lip tracking problem.

关键词： Robustness Shape Video sequences Lips Statistics Bayesian methods Noise shaping Skin Convergence Voting

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Fuzzy Vergence Control for an Active Binocular Vision System

Fuzzy Vergence Control for an Active Binocular Vision System

引用

IEEE international conference on Cybernetic Intelligent Systems

作者： Nikolaos Kyriakoulis Antonios Gasteratos Spyridon G. Mouroutsos Laboratory of Robotics and Automation Department of Production and Management Engineering School of Engineering Democritus University of Thrace Laboratory of Special Engineering Department of Electrical and Computer Engineering School of Engineering Democritus University of Thrace

ISBN: (纸本)9781424429141

Vergence control in binocular vision systems involves the adjustment of the angle between the two cameras' axes so that they are both fixated at the same point of interest. Vergence enables stereo vision systems to perceive depth and to acquire obstacle maps. Vergence movement is directly related to the binocular fusion. Additionally, the decision for convergence or divergence is extracted either by motion affine models or by mathematical ones. In this paper, a new method for extracting the cameras' movement direction, for verge or diverge, is presented. the movement decision is performed by a fuzzy control system, the inputs of which are the zero-mean normalized cross correlation (ZNCC) and the depth estimations at each time step. the suggested system can be used in any active binocular system and is computationally inexpensive. Moreover, the proposed system is independent to a priori camera calibration.

关键词： Vergence angle Zero mean normalized cross correlation Fuzzy logic binocular convergence Fuzzy logic computer vision Binocular vision fuzzy control systems new methods camera calibration Diverge BINOCULARS Cameras

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Solving the Inverse Kinematics Problem Symbolically by Means of Knowledge-Based and Linear Algebra-Based methods

Solving the Inverse Kinematics Problem Symbolically by Means...

引用

12th IEEE international conference on Emerging Technologies and Factory automation (ETFA 2007), vol.3

作者： Michael Wenz Heinz Worn Institute for Process Control and Robotics Universität Karlsruhe Karlsruhe Germany

the construction of kinematics models by hand is often a tedious and error-prone process. this paper presents an overview of the Organic Robot Control project. One main goal of the project is to automate the computation of closed-formed solutions for both the forward and inverse kinematics of general industrial manipulators. For simple manipulator geometries, we use rule-based programming techniques to obtain a closed-form solution. For complicated geometries, we use elimination techniques based on the computation of Groebner basis. In so doing we convert a complicated coupled transcendental set of kinematics equations into a univariate polynomial. this polynomial can much easier be solved. the generated analytic models fulfill real time requirements and can be parallelized very well.

关键词： Kinematics Manipulators Computational geometry Polynomials Robot control Computer industry Construction industry Robot programming Closed-form solution Equations

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Vision for Cognitive Systems: A New Compound Concept Connecting Natural Scenes with Cognitive models

Vision for Cognitive Systems: A New Compound Concept Connect...

引用

IEEE international conference on Industrial Informatics (INDIN)

作者： Peter Michael Goebel Markus Vincze Vienna University슠of슠Technology Austria Automation and Control Institute Vision for Robotics Laboratory University of Technology Vienna Austria

Vision, as a key perceptional capability for cognitive systems relates to rather difficult problems -such as visual object recognition, representation, categorization, and scene understanding. State-of-the-art solutions, using object appearance based models, already reached certain maturity. they achieve excellent recognition performance and provide learning structures that are subsequently utilized for object recognition and tracking. However, in context of object topology understanding for cognitive tasks, these methods cannot be directly compared with human performance, because it is obvious that appearance based methods do not contribute to understanding of structures in 3D. Research findings from infant psychology and animal investigation give evidence for using hierarchical models of object representation, based on image primitives e.g. such as edges, corners, shading or homogeneity of object colors. It is the objective of this paper to present an approach based on both, findings from biological studies and cognitive science, as enablers for autonomous cognitive investigation of natural scenes and their understanding. We present the architecture of a compound cognitive framework and its first behavioral level with the implementation of a vision model of the mammalian striate visual cortex in five layers. the proposed implementation is exemplified with an object similar to the Necker cube.

关键词： Machine vision Joining processes Layout Object recognition Biological system modeling Topology Humans Animal structures Pediatrics Psychology

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