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第25届中国控制与决策会议

作者： Chunhui Zhao Youxian Sun State Key Laboratory of Industrial Control Technology Department of Control Science and Engineering Zhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781467355322

As batches operate at different statuses across different phases, it can be advantageous to partition the whole batch process into different phases and characterize them separately by multiple local phase models. The conventional clustering-based phase division algorithm overlooks the time sequence of batch operation which thus may mix different time segments located within a batch into one phase. Moreover, it is hard to capture the transitions between neighboring phases. In the present work, an automatic step-wise sequential phase division algorithm is developed to capture the changes of process characteristics along time direction within each batch. Its theoretical support is framed and the related statistical characteristics are analyzed. Using this algorithm, major phases are captured and the transition regions are separated from them as separate time regions. Thus, different statistical models are developed to reflect their time-varying characteristics. The online monitoring system is set up, which can realtime judge the affiliation of each new sample and check its status by adopting the proper statistical model. Comprehensive comparison is conducted between the proposed algorithm and clustering-based phase division algorithm. Its feasibility and performance are illustrated by an injection molding process which presents typical multiphase nature as well as transition characteristics.

关键词： multiphase batch processes sequential phase partition transition patterns online process monitoring multivariate statistical analysis.

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Performance Monitoring of the Data-driven Subspace Predictive control systems Based on Historical Objective Function Benchmark

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自动化学报 2013年第5期39卷 542-547页

作者：王陆李柠李少远 Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of China

In this paper, a historical objective function benchmark is proposed to monitor the performance of data-driven subspace predictive control systems. A new criterion for selection of the historical data set can be used to monitor the controller0s performance, instead of using traditional methods based on prior knowledge. Under this monitoring framework, users can define their own index based on different demands and can also obtain the historical benchmark with a better sensitivity. Finally, a distillation column simulation example is used to illustrate the validity of the proposed algorithms.

关键词：预测控制系统性能监控数据驱动子空间历史基准监视控制器目标函数

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Data-driven Predictive control for the Industrial Processes with Multiphase and Transition

Data-driven Predictive Control for the Industrial Processes ...

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第25届中国控制与决策会议

作者： Hua Yang Shaoyuan Li College of Information Science and Engineering Ocean University of China Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467355339

Processes with multiphase are commonly found in process industries. Process dynamics and correlations among variables tend to change with the transitions across such phases. In this paper, we propose a new data-driven predictive control strategy with the consideration of the important multiphase feature. The method aims to feature the multiphase data and use the data to design the controller. First, the data is divided and weighted based on the multiple phases and transitions. Through the minimal image representation, the data-driven prediction of future trajectory can be obtained and thus the computation of dynamic optimization. In the proposed controller, data Hankel matrices is direct incorporated in the predictive control laws, without a model or an intermediate step to meet the given performance specifications. Finally, the proposed predictive controller is demonstrated on a multiphase process.

关键词： Multiphase predictive control data-driven

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Two-degree-of-freedom controller Design for MIMO systems with Multiple Time Delays Based on Inversing Decoupling

Two-degree-of-freedom Controller Design for MIMO Systems wit...

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第三十二届中国控制会议

作者： ZHANG Wei SUN Boi ZHANG Xi ZHANG Weidongi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Guangdong power grid corporation

ISBN: (纸本)9781479900305

In this paper,a two-degree-of-freedom(TDOF) controller design method for multi-inputs multi-outputs(MIMO) system with multiple time delays based on inversing decoupling is ***,an inversing decoupling method based on the factorization of the plant is ***,the H2 optimal controller design method is applied to the decoupled single-input/single-output(SISO) system after the system has been ***,a TDOF controller is designed for the decoupled closed-loop *** with other developed methods,the proposed design method has two main advantages. One is that the design procedure is simple and the obtained controllers are given in analytical *** other is that better performance can be achieved since the TDOF control structure can isolate the disturbance from the *** are provided to illustrate the effectiveness of the proposed design approach.

关键词： TDOF MIMO multiple time delays inverse decoupling H2 optimal control

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LBP-based hierarchical sparse patch learning for face recognition

LBP-based hierarchical sparse patch learning for face recogn...

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2013 International Conference on Image processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013

作者： Zhao, Yue Su, Jianbo Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

ISBN: (纸本)1601322534

Local Binary Pattern (LBP) features and its variants are computed on the patches with the fixed positions and a fixed size in images, while the limited variety of the size and position cannot accurately measure the nature of face image. In this paper, we propose a new learning method, Hierarchical Sparse Patch Learning (HSPL), to select face patches with different positions and sizes for face recognition. HSPL employs a sparse learning model to hierarchically select patches at two levels: in level 1 the optimal patch candidates are figured out, while in level 2 the optimal patches from the candidates are obtained. LBP features are extracted from the optimal patches to recognize faces. Experimental results show that the proposed method is more efficient and achieves higher recognition rate than the other two compared methods. © 2013 CSREA Press. All rights reserved.

关键词： Local binary pattern

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A Cloaking-Based Approach to Protect Location Privacy in Location-Based Services

A Cloaking-Based Approach to Protect Location Privacy in Loc...

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第三十三届中国控制会议

作者： Zheng Jiangyu Tan Xiaobin Cliff Zou Niu Yukun Zhu Jin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Department of Automation University of Science and Technology of China Department of Electrical Engineering and Computer Science University of Central FloridaOrlandoFL 32816-2362

ISBN: (纸本)9781479947249

With the widespread use of mobile devices, the location-based service(LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a user expects to report his own location as far as possible away from his real location to protect his location privacy. On the other hand, in order to obtain high quality of service(QoS), users are required to report their locations as accurate as possible. To achieve the dedicated tradeoff between privacy requirement and QoS requirement, we propose a novel approach based on cloaking technique. We also discuss the disadvantage of the traditional general system model and propose an improved model. The basic idea of our approach is to select a sub-area from the generated cloaking area as user's reported location. The sub-area may not contain a user's real location,which prevents an adversary from performing attack with side information. Specifically, by defining an objective function with a novel location privacy metric and a QoS metric, we are able to convert the privacy issue to an optimization problem. Then, location privacy metric and QoS metric are given. To reduce the complexity of the optimization, a heuristic algorithm is *** privacy-preserving analysis and comparison with related work [8], we demonstrate the effectiveness and efficiency of our approach.

关键词： Location-based Services,Location Privacy,k-anonymity,Cloaking Area

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Optimization for family energy consumption in real-time pricing environment

Optimization for family energy consumption in real-time pric...

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2012 International Conference on Emerging Technologies for information systems, Computing, and Management, ICM 2012

作者： Wu, Weipo Yang, Genke Pan, Changchun Ju, Changjiang Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781461470090

In order to help consumers adapt to electricity consumption in real-time electricity pricing environment, an energy consumption scheme is proposed in this paper. This scheme focuses on the prediction, modeling and optimization for family energy consumption. A method based on support-vector machine (SVM) is used to predict the real-time price (RTP) and the optimization model divides every hour into equal time slots and thus provides more opportunities to schedule household appliances in proper working time. Then the simulation results show that the proposed optimal control model reduces the daily electricity expenditures. © 2013 Springer Science+Business Media New York.

关键词： Costs

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Anti-windup Design for Active Disturbance Rejection control

Anti-windup Design for Active Disturbance Rejection Control

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第三十三届中国控制会议

作者： Xiongjun Wu Jiaoni Pang Tao Yang The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China ACCESS Linnaeus Centre School of Electrical Engineering Royal Institute of Technology

ISBN: (纸本)9781479947249

An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection control(ADRC) mechanism, to deal with the input saturation nonlinearity and meanwhile reject the disturbance automatically by using Extended State Observer(ESO). The output of anti-windup compensator is treated as a part of unknown disturbances and is introduced into the ESO, which can online observe both internal and external disturbances(parameter uncertainties and model mismatches). The controller input is yielded by using a nonlinear feedback combination, and it is used to compensate the integrator windup caused by the saturation nonlinearity element. On the other hand, in order to determine the parameters of the ESO and the anti-windup compensator feedback gain, the L2 gain is adopted. The effectiveness and the robustness against model and parameter uncertainties of the proposed method is verified by an example of the seeker platform.

关键词： Actuator saturation,Anti-windup design,Active disturbance rejection,Extended State Observer(ESO),Tracking Differentiator

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Enhancing the Effectiveness of Fungicides by Optimizing Their Combinations

Enhancing the Effectiveness of Fungicides by Optimizing Thei...

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第26届中国控制与决策会议

作者： Xiang Wang Jia Ma Xiaowei Li Xiaodong Zhao Zongli Lin Jie Chen Zhifeng Shao Department of Automation and Key Laboratory of System Control and Information Processing of the Ministry of EducationShanghai Jiao Tong University Department of Resource and Environmental Science School of Agriculture and BiologyShanghai Jiao Tong University School of Biomedical Engineering Shanghai Jiao Tong University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

In controlling biological diseases, it is often more potent to use a combination of agents than using individual ones. However, the number of possible combinations increases exponentially with the number of agents and their concentrations. It is prohibitive to search for effective agent combinations by trial and error as biological systems are complex and their responses to agents are often a slow process. This motivates to build a suitable model to describe the biological systems and help reduce the number of experiments. In this paper, we consider the use of fungicides to inhibit Bipolarismaydis and construct models that describe the responses to fungicide combinations. Three data-driven modeling methods, the polynomial regression, the artificial neural network and the support vector regression, are compared based on the experimental data of the inhibition rates of the southern corn leaf blight with different fungicide combinations. The analysis of the results demonstrates that the support vector regression is best suited to the construction of the response model in terms of achieving better prediction with fewer experiments.

关键词： agent combinations,complex system,data-driven model,polynomial regression,artificial neural network,support vector regression

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A fast network partition method for large-scale urban traffic networks

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控制理论与应用（英文版） 2013年第3期11卷 359-366页

作者： Zhao ZHOU Shu LIN Yugeng XI Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education

In order to control the large-scale urban traffic network through hierarchical or decentralized methods, it is necessary to exploit a network partition method, which should be both effective in extracting subnetworks and fast to compute. In this paper, a new approach to calculate the correlation degree, which determines the desire for interconnection between two adjacent intersections, is first proposed. It is used as a weight of a link in an urban traffic network, which considers both the physical characteristics and the dynamic traffic information of the link. Then, a fast network division approach by optimizing the modularity, which is a criterion to distinguish the quality of the partition results, is applied to identify the subnetworks for large-scale urban traffic networks. Finally, an application to a specified urban traffic network is investigated using the proposed algorithm. The results show that it is an effective and efficient method for partitioning urban traffic networks automatically in real world.

关键词： Traffic signal control Large-scale urban traffic networks Network partition

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