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European control Conference

作者： Ruben Marti Sergio Lucia Daniel Sarabia Radoslav Paulen Sebastian Engell Cesar de Prada Department of Systems Engineering and Automatic Control University of Valladolid Process Dynamics and Operations Group Technische Universitt Dortmund Department of Electromechanical Engineering Escuela Politecnica Superior University of Burgos

ISBN: (纸本)9781467371605

This paper presents an algorithmic development in the framework of computationally efficient robust Non-linear Model Predictive control (NMPC) which deals with a parametric plant-model mismatch, where the description of the evolution of the uncertainty is done using a scenario tree, known as multi-stage approach. In order to reduce the computational time and memory requirements of the multistage NMPC, the calculations of the optimal control inputs can be done scenario-wise in parallel. These parallelized calculations must enforce the satisfaction of the non-anticipativity constraints, which is negotiated iteratively among the scenarios using Lagrangean or price-driven decomposition. The main challenge in using such scheme is the determination of the values of the aggregate variables that are used to coordinate the scenario-wise computations for convergence to the feasibility of the non-anticipativity constraints. The proposed approach uses parametric sensitivities of the optimal model states with respect to the control inputs which are used for the iterative determination of the values of aggregated variables. The proposed method achieves good performance and faster convergence compared to traditional decomposition schemes. The potential of the approach is demonstrated in simulation example of an hydrodesulphurisation unit.

关键词： control input Nonlinear predictive control nonlinear model predictive control distributed algorithms memory requirements Converge computational time Parametric

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LS/IV parametric identification for continuous and delay chemical reactor

LS/IV parametric identification for continuous and delay che...

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International Conference on systems and control (ICSC)

作者： Sameh Ben Mohamed Boumedyen Boussaid Naceur Abdelkrim Charfeddine Tahri Electrical Engineering and Automatic Control department University of Gabes Gabes Tunisia Skhira plant Tunisian Chemical Group Sfax Tunisia

Because of the dependence of the parameters in the chemical reactor industries to the raw material used in processes, an online identification of the process parameters is necessary to adjust the process control loops. This paper deals with continuous time and delay system identification of the chemical reactor. The identification of linear and single input-single output (SISO) system is based on the least square (LS) method, in which the output is corrupted by a non Gaussian white noise sequence. The least square method is perhaps the most commonly used parametric identification method, but it is biased even for a white measurement noise. To remove this bias we use the instrumental variable (IV) method. Results obtained indicate that the proposed algorithm provides more accurate estimated parameters.

关键词： Mathematical model Estimation Delays Chemical reactors Instruments Chemicals Inductors

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Real-time and model-free object tracking using particle filter with Joint Color-Spatial Descriptor

Real-time and model-free object tracking using particle filt...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Shile Li Seongyong Koo Dongheui Lee Chair of Automatic Control Engineering Department of Electrical Engineering and Computer Engineering Technische Universitat Munchen Munich Germany Autonomous Intelligent Systems (AIS) Group Computer Science Institute VI University of Bonn Germany

This paper presents a novel point-cloud descriptor for robust and real-time tracking of multiple objects without any object knowledge. Following with the framework of incremental model-free multiple object tracking from our previous work [5][7][6], 6 DoF pose of each object is firstly estimated with input point-cloud data which is then segmented according to the estimated objects, and incremental model of each object is updated from the segmented point-clouds. Here, we propose Joint Color-Spatial Descriptor (JCSD) to enhance the robustness of the pose hypothesis evaluation to the point-cloud scene in the particle filtering framework. The method outperforms widely used point-to-point comparison methods, especially in the partially occluded scene, which is frequently happened in the dynamic object manipulation cases. By means of the robust descriptor, we achieved unsupervised multiple object segmentation accuracy higher than 99%. The model-free multiple object tracking was implemented by using a particle filtering with JCSD as a likelihood function. The robust likelihood function is implemented with GPU, thus facilitating real-time tracking of multiple objects.

关键词： Data models Robustness Adaptation models Object tracking Three-dimensional displays Image color analysis Real-time systems

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Real-time bug-like dynamic path planning for an articulated vehicle

Lecture Notes in Electrical Engineering

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Lecture Notes in Electrical engineering 2014年 325卷 201-215页

作者： Nayl, Thaker Nikolakopoulos, George Gustafsson, Thomas Automatic Control Group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå97187 Sweden

This article proposes a novel real time bug like algorithm for performing a dynamic smooth path planning scheme for an articulated vehicle under limited and sensory reconstructed surrounding static environment. In the general case, collision avoidance techniques can be performed by altering the articulated steering angle to drive the front and rear parts of the articulated vehicle away from the obstacles. In the presented approach factors such as the real dynamics of the articulated vehicle, the initial and the goal configuration (displacement and orientation), minimum and total travel distance between the current and the goal points, and the geometry of the operational space are taken under consideration to calculate the update on the future way points for the articulated vehicle. In the sequel the produced path planning is iteratively smoothed online by the utilization of Bezier lines before producing the necessary rate of change for the vehicle’s articulated angle. The efficiency of the proposed scheme is being evaluated by multiple simulation studies that simulate the movement of the articulated vehicle in open and constrained spaces with the existence of multiple obstacles. © Springer International Publishing Switzerland 2014.

关键词： Motion planning

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Identifying Biochemical Reaction Networks From Heterogeneous Datasets

Identifying Biochemical Reaction Networks From Heterogeneous...

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IEEE Annual Conference on Decision and control

作者： Wei Pan Ye Yuan Lennart Ljung Jorge Goncalves Guy-Bart Stan Centre for Synthetic Biology and Innovation and the Department of Bioengineering Imperial College London United Kingdom Department of Electrical Engineering and Computer Sciences UC Berkeley Division of Automatic Control Department of Electrical Engineering Linkoping University Sweden Control Group Department of Engineering University of Cambridge United Kingdom

ISBN: (纸本)9781479978878

In this paper, we propose a new method to identify biochemical reaction networks (i.e. both reactions and kinetic parameters) from heterogeneous datasets. Such datasets can contain (a) data from several replicates of an experiment performed on a biological system;(b) data measured from a biochemical network subjected to different experimental conditions, for example, changes/perturbations in biological inductions, temperature, gene knock-out, gene over-expression, etc. Simultaneous integration of various datasets to perform system identification has the potential to avoid non-identifiability issues typically arising when only single datasets are used.

关键词： Dataset Biochemical Reaction Biochemical network System identification Kinetic parameters gene overexpression experimental conditions Replicating

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Observer-Based control Design for a Class of Nonlinear systems Subject to Unknown Inputs: LMI Approach

Observer-Based Control Design for a Class of Nonlinear Syste...

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International Conference on control, Automation and systems

作者： Saleh S. Delshad Thomas Gustafsson Hamid Reza Karimi Ali Zemouche Control Engineering Group Lulea University of Technology Department of Engineering Faculty of Engineering and Science University of Agder Research Center for Automatic Control of Nancy University of Lorraine

ISBN: (纸本)9781479999767

This paper deals with the problem of observer-based controller design for a class of nonlinear systems subject to unknown inputs. A novel method is presented to design a controller using estimated state variables which guarantees all the state variables of the closed-loop system converge to the vicinity of the origin and stay there forever. This is done via satisfying several sufficient conditions in terms of nonlinear matrix inequalities. In light of linear algebra, particularly matrix decompositions, the achieved conditions will be converted to a Linear Matrix Inequality (LMI) problem to facilitate the procedure of computing the observer and controller gains. Finally, the effectiveness of the proposed method is illustrated by implementing on a highly nonlinear chaotic system.

关键词： Nonlinear systems Unknown Inputs Observer-Based control Design Linear Matrix Inequality

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InsERT: the Inspirational Expert Recommender Tool

InsERT: the Inspirational Expert Recommender Tool

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IEEE International Conference on Fuzzy systems

作者： Jennifer Nguyen Germán Sánchez-Hernández Núria Agell Cecilio Angulo GREC Research Group Industrial Engineering School Universitat Politècnica de Catalunya Barcelona Spain GREC Research Group ESADE Business School Ramon Llull University Barcelona Spain GREC Research Group Automatic Control Department Universitat Politècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781467374293

The continued growth in enterprise social networks is fueled by the need to enable productivity and innovation. Reducing the constraints to communication and knowledge sharing of a globally distributed workforce, will facilitate the workflow. People finder systems are one of the main solutions in enterprise social networks which are reducing these constraints leading to time and cost savings. Finding expertise efficiently helps organizations to unlock knowledge within the enterprise, solve problems, and identify collaborators. However, the following challenges still exist: validating expertise, determining responsiveness and accessibility, and managing expert profiles. In this paper, we propose the fuzzy OWA technique as a novel approach to ranking candidates in expertise search. We consider its application in open innovation intermediaries where the search for partners and expertise is at the center of the business model. In addition, we demonstrate its application in a software tool (InsERT) as part of a larger enterprise social network implementation.

关键词： InsERT Inspirational Expert Recommender Tool innovation

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Modelling and control of a semi-active suspension system

Modelling and control of a semi-active suspension system

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作者： Colina, A. Lerma, G. Cabanes, I. Iglesias, I. Department of Automatic Control and System Engineering University of the Basque Country Spain Industry and Transport Division Vehicle Dynamics Group Tecnalia Research and Innovation Spain

ISBN: (纸本)9789400774841

The suspension system is composed of several deformable elements such as springs and dampers, which connect the car body to wheels and absorb vibrations generated by road irregularities. The main purpose of suspension system is to isolate the vehicle body from disturbances in order to keep wheels in contact with the road surface to contribute to road holding, and in order to maximize passenger ride comfort. This paper describes a semi-active suspension system of 2 degrees of freedom (2DOF), typically referred to as a quarter car model. To design a suspension control system that improve ride comfort, dynamic modelling of semi-active suspension was developed. control strategies were implemented for these semi-active suspension systems using MATLAB® and Simulink® software. The results show that the semi-active suspension system controlled by a logical strategy minimizes vertical acceleration experienced by passengers, compared to passive suspension system. © Springer Science+Business Media Dordrecht 2014.

关键词： Wheels

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