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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Xinlan Guo Hongxia Zhao Mechanical and Electrical Engineering Department Nanjing Communications Institute of Technology The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Huawei Nanjing Institute

This paper design controller for the uncertain neutral delay system. The uncertain neutral delay system includes norm bounded uncertain system parameters and unknown constant delay. The paper uses uncertain neutral systems with structural features, and constructs appropriate Lyapunov function to obtain feedback control law. Compared with the previous methods for solving the Riccati equation, this method overcomes the shortcoming of Riccati equation emphasizing the center solution. Simulation results show that, the conservatism of the controller designed in this paper is reduced, and the controller easy to operate and application.

关键词： Robust H∞ control neutral system uncertain time delay feedback control

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Plant growth architecture and production dynamics : A set of e-learning resources

Plant growth architecture and production dynamics : A set of...

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2016 IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications, FSPMA 2016

作者： Jaeger, Marc De Reffye, Philippe Sabatier, Sylvie Caraglio, Yves Krit, Hatem Lafond, Marie-Helene Letort, Veronique Heuvelink, Ep Motisi, Matacha Zhang, BaoGui Kang, Mengzhen CIRAD AMAP Unit Montpellier34398 France University of Montpellier LIRMM ICAR Montpellier34095 France CentraleSupélec MAS Châtenay-Malabry92290 France WURL HPC Group Wageningen6700AA Netherlands CIRAD Pest and Disease Unit Montpellier34398 France Key Laboratory of Plant-Soil Interactions College of Resources and Environment China Agricultural University Beijing100193 China State Key Laboratory of Management and Control for Complex Systems LIAMA CASIA Beijing100190 China Qingdao Academy of Intelligent Sciences Qingdao266109 China

ISBN: (纸本)9781509016594

FSPM Plant and crop models are popular in the research community and there is increasing interest in their applications, from yield prediction to crop management optimization. A wide range of approaches and their software implementation can be found in the literature, with a large diversity in modelling scale (from plant organ to plot levels) and scope (structural, functional or both), as well as generic or specific aim. However, most of these approaches rely on similar key assumptions and methods related to different disciplines: Botany for plant structure, eco-physiology for production, statistics and dynamic system theory for parameter identification and estimation. Web disseminated plant and crop models learning supports are not numerous, often specific, and partial. We present here a set of e-learning resources, named 'Plant growth architecture and production dynamics' which describes the main notions from plant morphology and architecture, eco-physiology and applied mathematics necessary to the understanding of most plant and crop models, and their typology. In this paper, after an overview of existing learning resources on plant and crop modelling which, we believe, might be of interest for the whole research community, we present the proposed resource, which uses the GreenLab model as illustration, organized as follows: •Five standalone introductive disciplinary resources: Botanical notions, assumptions in eco-physiology, basis in data processing, introduction to models, introduction to GreenLab •An FSPM example in more details: GreenLab positioning, its basis, structure modelling, production modelling, and applications including model fitting and a study case •Tools: Inline (for structure analysis and statistics), online (access to fitters for instance) and access to download simulators and their documentation •Glossary, bibliography, web site collection, and a pedagogic kit for instructors Supported by the French Sustainable Development Virtual University

关键词： Glossaries

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Adaptive Dynamic Programming Based Fault Compensation control for Nonlinear systems with Actuator Failures

Adaptive Dynamic Programming Based Fault Compensation Contro...

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International Joint Conference on Neural Networks

作者： Bo Zhao Derong Liu Yuanchun Li Guang Shi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing Department of Control Science and Engineering Changchun University of Technology

ISBN: (纸本)9781509006212

This paper develops a novel fault compensation control scheme based on adaptive dynamic programming for nonlinear systems with actuator failures. The control scheme consists of a policy iteration algorithm and a fault compensation. For fault-free dynamic models, the Hamilton-Jacobi-Bellman equation is solved by policy iteration algorithm via constructing a critic neural network, and then the approximate optimal control policy can be derived directly. On the other hand, the online fault compensation is achieved without the fault detection and isolation mechanism by reconstructing the actuator failure. The closed-loop system is guaranteed to be asymptotically stable based on Lyapunov stability theorem. Two simulation examples are given to demonstrate the effectiveness of the present fault compensation control scheme.

关键词： Iterative algorithms Nonlinear systems compensator control dynamic programming Defect detection faults actuators system failures

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Event-based state estimation of discrete-state hidden Markov models

Event-based state estimation of discrete-state hidden Markov...

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作者： Shi, Dawei Elliott, Robert J. Chen, Tongwen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China School of Mathematical Sciences University of Adelaide SA5005 Australia Haskayne School of Business University of Calgary CalgaryAB Canada Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

The state estimation problem for hidden Markov models subject to event-based sensor measurement updates is considered in this work, using the change of probability approach. We assume the measurement updates are transmitted through wired or wireless communication networks. For the scenarios with reliable and unreliable communication channels, analytical expressions for the probability distributions of the states conditioned on all the past point- and set-valued measurement information are obtained. Also, we show that the scenario with a lossy channel, but without the event-trigger, can be treated as a special case of the reliable channel results. Based on these results, closed-form expressions for the estimated communication rates under the original probability measure are presented, which are shown to be the ratio between a weighted 1-norm and the 1-norm of the unnormalized conditional probability distributions of the states under the new probability measures constructed. Implementation issues are discussed, and the effectiveness of the results is illustrated by numerical examples and comparative simulations. © 2015 Elsevier Ltd. All rights reserved.

关键词： Hidden Markov models

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Kinematics and dynamics modelling of all terrain articulated tracked vehicles

Kinematics and dynamics modelling of all terrain articulated...

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World Congress on intelligent control and Automation (WCICA)

作者： Hao Lin Wei Lin En Li Zize Liang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Zhenhai Refining & Chemical Company Dep. V Sinopec Ningbo China

ISBN: (纸本)9781467384155

This paper presents an extended kinematics and dynamics of the articulated tracked vehicles (ATV) used in many applications. The velocity of the front and the rear vehicle are firstly analysed and the kinematics of ATV is built, according to which the steer radius and the track velocity can be obtained. Then we analyse the force and moment acting on the ATV running on the firm ground and the soft ground, respectively. And a unified dynamics is established in a matrix form. To show the motion performance of the ATV, simulations are performed and the results are further presented.

关键词： Vehicles Force Vehicle dynamics Kinematics Dynamics Mathematical model Tracking

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Contributions of Social Manufacturing to Sustainable Apparel Industry

Contributions of Social Manufacturing to Sustainable Apparel...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Babak Mohajeri Timo Nyberg Jesse Karjalainen Mark Nelson Gang Xiong Aalto University Department of Industrial Engineering and Management Human Sciences and Technologies Advanced Research Institute (H-STAR)Stanford University The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science

The global apparel and textile market has been changed considerably during the recent years. At the one hand, new trends and consumer preferences for different styles and fashion products emerge continuously, thus the apparel industry becomes more mass customized. On the other hand, attention to social and environmental sustainability has been dramatically increased in the entire industry. However, the current fast-changing fashion trends result to significant environmental and resource depletion problems in the textile lifecycle. As a result, the apparel industry should consider sustainable manufacturing strategies. The current options such as organic fibers and environmentally safe dyes seem promising. Nonetheless, there are significant challenges for apparel manufacturers and retailers to capitalize sustainability. To address these problems, in this paper, we develop a conceptual model of Social Manufacturing for the apparel industry. We study the current value chain of the apparel industry and identify its challenges from the sustainability's view. Then, we propose a new model to improve the sustainability throughout the value chain of the apparel industry

关键词： Social Manufacturing Apparel Industry Value chain sustainability

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Multi-player pursuit–evasion games with one superior evader

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Automatica 2016年 71卷 24-32页

作者： Jie Chen Wenzhong Zha Zhihong Peng Dongbing Gu School of Automation Beijing Institute of Technology Beijing 100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China School of Computer Science and Electronic Engineering University of Essex Colchester CO4 3SQ UK

Inspired by the hunting and foraging behaviors of group predators, this paper addresses a class of multi-player pursuit–evasion games with one superior evader, who moves faster than the pursuers. We are concerned with the conditions under which the pursuers can capture the evader, involving the minimum number and initial spatial distribution required as well as the cooperative strategies of the pursuers. We present some necessary or sufficient conditions to regularize the encirclement formed by the pursuers to the evader. Then we provide a cooperative scheme for the pursuers to maintain and shrink the encirclement until the evader is captured. Finally, we give some examples to illustrate the theoretical results.

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Image Clustering Based on Deep Sparse Representations

Image Clustering Based on Deep Sparse Representations

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IEEE Symposium Series on Computational Intelligence

作者： Le Lv Dongbin Zhao Qingqiong Deng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781509042418

Currently, the supervised trained deep neural networks (DNNs) have been successfully applied in several image classification tasks. However, how to extract powerful data representations and discover semantic concepts from unlabeled data is a more practical issue. Unsupervised feature learning methods aim at extracting abstract representations from unlabeled data. Large amount of research works illustrate that these representations can be directly used in the supervised tasks. However, due to the high dimensionality of these representations, it is difficult to discover the categorical concepts among them in an unsupervised way. In this paper, we propose combining the winner-take-all autoencoder with the bipartite graph partitioning algorithm to cluster unlabeled image data. The winner-take-all autoencoder can learn the additive sparse representations. By the experiments, we present the properties of the sparse representations. The bipartite graph partitioning can take full advantage of them and generate semantic clusters. We discover that the confident instances in each cluster are well discriminated. Based on the initial clustering result, we further train a support vector machine (SVM) to refine the clusters. Our method can discover the categorical concepts rapidly and the experiment shows that the clustering performance of our method is good.

关键词： supervised trained deep

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Neural-network-based robust optimal control of uncertain nonlinear systems using model-free policy iteration algorithm

Neural-network-based robust optimal control of uncertain non...

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International Joint Conference on Neural Networks

作者： Chao Li Ding Wang Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing 100083 China

ISBN: (纸本)9781509006212

In this paper, we establish a robust optimal control law for a class of continuous-time uncertain nonlinear systems by using a neural-network-based model-free policy iteration approach. The robust control law of the original uncertain nonlinear system is derived by adding a feedback gain to the optimal control law of the nominal system. It is proven that this robust control law can achieve optimality under a specified cost function. Then, the neural-network-based model-free policy iteration algorithm is developed to solve the Hamilton-Jacobi-Bellman equation corresponding to the nominal system without system dynamics. The actor-critic technique and the least squares implementation method are used to obtain the optimal control policy of the nominal system. A numerical simulation is given to verify the applicability of the present robust optimal control scheme.

关键词： Optimal control Cost function Mathematical model Heuristic algorithms Robustness Robust control Nonlinear systems

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High-precision NURBS interpolation algorithm based on the bisection method 34

High-precision NURBS interpolation algorithm based on the bi...

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34th Chinese control Conference, CCC 2015

作者： Zhongyi, Zheng Chao, Yang Fengshui, Jing Guodong, Yang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789881563897

For a high precision Non-Uniform Rational B-Spline (NURBS) interpolator, calculating the parameter of the next path interpolating point is an indispensable step, which affects feedrate fluctuation. This paper presents a new, simple and precise interpolation algorithm for parameter curve which adopts first-order Taylor's expansion, and then make use of the bisection method to achieve accurate path parameters. In the meanwhile, the interpolator is restricted from geometric and kinematical constraints. A simulation study is conducted to demonstrate the advantages of proposed interpolation algorithm compared with other algorithms for the parametric curves represented in the NURBS form. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Interpolation Machining NURBS Precision

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