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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Correction of Images Projected on Non-White Surfaces Based on Deep Neural Network 14

Correction of Images Projected on Non-White Surfaces Based o...

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14th International Conference on Digital Image processing, ICDIP 2022

作者： Wang, Zewei Zhang, Jingjing Du, Xingzhuo Cao, Sihua Wei, Wenxuan School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9781510657564

When projecting onto a non-white surface, the projected image is distorted or color mixing by complex luminance and chrominance information, which makes the projection result different from the visual perception of the human eye. The purpose of projection image correction is to remove these effects, and traditional solutions usually estimate parameters from the collected projection samples, compute an inverse model of the projection imaging process, and try to fit a correction function. In this paper, a deep neural network-based projection image correction network (PICN) is designed to implicitly learn complex correction functions. PICN consists of a U-shaped backbone network, a convolutional neural network that extracts projected surface features, and a perceptual loss network that optimizes the correction results. Such a structure can not only extract the deep features and surface interference features of the projected image, but also make the corrected projected image more in line with human visual perception. In addition, we built a projector-camera system under the condition of a fixed global illumination environment for verification experiment, and proved the effectiveness of the proposed method by calculating the evaluation metrics of projected images before and after correction. © 2022 SPIE.

关键词： Deep neural networks

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A Finite-Time Tracker for Nonholonomic systems Using Recursive Singularity-Free FTSM

A Finite-Time Tracker for Nonholonomic Systems Using Recursi...

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2011 American control Conference (ACC)

作者： Saleh Mobayen Mohammad Javad Yazdanpanah Vahid Johari Majd Intelligent Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Moalem University Tehran Iran Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Iran

A novel recursive singularity free FTSM (Fast Terminal Sliding Mode) strategy for finite time tracking control of nonholonomic systems is proposed. As a result, the singularity problem around the origin resulting from the fractional power of conventional terminal sliding mode is resolved. Simulation results are given for two benchmark examples of extended chained-form nonholonomic systems: a wheeled mobile robot and an underactuated surface vessel. The results show the effectiveness of the proposed strategy.

关键词： Mobile robots Trajectory Mathematical model Equations Convergence Tracking

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Evaluation of functional connectivity in control and ADHD subjects by generalized canonical correlation and probabilistic independent component analysis

Evaluation of functional connectivity in control and ADHD su...

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2011 18th Iranian Conference of Biomedical Engineering, ICBME 2011

作者： Lashkari, Amirehsan Soltanian-Zadeh, Hamid Hosseinzadeh, Gholamali Elec. and Comp. Eng. Dept. Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9781467310055

Functional connectivity can be evaluated by temporal correlation between spatial neurophysiologic events or correlation between neural activities of brain regions. Unlike anatomical connectivity which represents physical connections between two brain regions, functional connectivity investigates interactions between brain regions. In this study, we implemented and evaluated Probabilistic Independent Component Analysis (PICA) and generalized Canonical Correlation Analysis (gCCA) on resting state data of healthy subjects and subjects with ADHD disorders from NITRC database. This was done to detect brain functional connectivity and compare the results in normal and diseased subjects. In addition, speed of the methods was compared. Our study shows that relative to PICA, gCCA has higher precision and accuracy and lower computational complexity and run time in addition to capability of extracting more reproducible statistical maps in both control and ADHD subjects. © 2011 IEEE.

关键词： Independent component analysis

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Multi-robot distributed cooperative monitoring of mobile targets 3rd

Multi-robot distributed cooperative monitoring of mobile tar...

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3rd International Conference on Intelligence Science, ICIS 2018

作者： Jiang, J.Q. Xin, B. Dou, L.H. Ding, Y.L. School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9783030013127

Cooperative monitoring targets of mobile robots is of great importance in military, civil, and medical applications. In order to achieve multi-robot coordinated monitoring, this paper proposes a new distributed path planning algorithm. In this algorithm, a method of dynamic sequential decision making is used firstly to determine which robots should be moved to the neighbourhoods of the target path. A distributed cooperative path planning algorithm is then proposed in which the robots can only utilize their local information to make the joint monitoring areas of robots cover the target path. To reduce the chance of detection and ensure enough time to implement monitoring handover, our distributed algorithm can guarantee enough overlapped monitoring areas between adjacent robots. The effectiveness of the algorithm was verified by simulation experiments and a comparison experiment in typical scenarios. © IFIP International Federation for Information processing 2018.

关键词： Monitoring

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An adaptive fault detection strategy for Cz crystal growth process

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

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Realization of Nonlinear Adaptive Compliance: Towards Energy Efficiency in Cyclic Tasks

Realization of Nonlinear Adaptive Compliance: Towards Energy...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Rezvan Nasiri Arjang Ahmadi Majid Nili Ahmadabadi Cognitive Systems Laboratory Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

Due to the nonlinearity of dynamical equations in robotic systems, nonlinear compliance has more potential for energy consumption reduction. Moreover, the legged robots require adaptive structures so as to maximize their efficiency w.r.t. the new environments and gaits. Therefore, having nonlinear adaptive compliance is essential in legged robots. In this paper, we take one step towards the realization of nonlinear compliances with adaptable torque-deflection profiles. So as to achieve this goal, we present a mechanism which consists of four linear extension springs. Changing the arrangement of linear springs can adapt the compliance profile to the desired one. In addition, to optimize the arrangement of linear springs in an online manner, an adaptation rule is presented. The proposed adaptation rule adapts the compliance profile such that the actuator's torque and consequently the energy consumption are reduced. The performance of presented adaptation rule for actuator's torque minimization is analyzed by means of simulations. In simulations, we observed that the adaptation rule not only minimizes the energy consumption but also improves the tracking performance of the controller. Finally, to realize nonlinear adaptive compliance, a prototype of the presented mechanism is designed and constructed.

关键词： Torque Springs Robots Actuators Energy consumption Task analysis Mathematical model

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An expert system realization of Adaptive Autonomy in electric Utility Management Automation

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Journal of Applied Sciences 2009年第8期9卷 1524-1530页

作者： Fereidunian, A. Zamani, M.A. Lesani, H. Lucas, C. Lehtonen, M. Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Iran Power Systems and High Voltage Laboratory Helsinki University of Technology FI-02015 HUT Finland

Earlier we introduced a novel framework for implementation of Adaptive Autonomy (AA). This study presents an expert system realization of the AA framework, referred to as Adaptive Autonomy Expert System (AAES). The proposed AAES is based on the extracted rules from the Expert's Judgment on proper Levels of Automation (LOA) for various environmental conditions, modeled as Performance Shaping Factors (PSFs). Decision fusion method is used as expert system inference engine, where eight decision fusion methods arc developed as prospective ones. The AAES is realized in the practical case of electric power Utilily Management Automation (UMA) for the Greater Tehran Electricity Distribution Company (GTEDC). The practical list of PSFs and the judgments of GTEDC's experts are used as the expert system rule base in this research. The results of implementing the proposed AAES to GTEDC's network are evaluated according to two criteria: average error and error margin. Five out of eight decision fusion methods arc proven to be suitable inference engines, due to both criteria. Evaluation of the results shows that the proposed AAES can estimate proper LOAs for GTEDC's UMA system, which change due to the changes in PSFs;thus providing a dynamic (adaptive) LOA scheme for UMA. © 2009 Asian Network for Scientific Information.

关键词： Engines

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Learning Cooperative Object Pushing with Variable Contact Point

Learning Cooperative Object Pushing with Variable Contact Po...

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2007 IEEE/ASME International Conference on advanced intelligent Mechatronics, Pages 805-1210

作者： Abdol Hossein Aminaiee Majid Nili Ahmadabadi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence Department of Electerical and Computer Engineering University of Tehran

ISBN: (纸本)9781424412631;1424412633

Learning in multi-agent environments where each agent's action directly affects other agents would be an important matter and a complicated task. To reduce the learning time and simplifying the learning process, it is suitable to learn individual skills and then provide cooperation and coordination utilizing the learned individual skills. In the approach proposed in this paper, agents benefit from their individual knowledge obtained in the individual learning phase to cooperate with other agents. Cooperative object pushing system is used as a testbed to our proposed method where cooperation and coordination between agents are needed in these systems. Agents independently learn to push the object to the target by using the proposed fuzzy reinforcement learning method. Agents attain their cooperative behaviors properly making use of the coded knowledge in the Q-table. Simulation and experimental results show that by interpreting the knowledge in the Q-table, agents can achieve high level behaviors with a high degree of cooperation.

关键词： Agents Learning Point contacts pushing variable contact

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Optimal tracking cooperative control for multi-agent systems with periodic sampling via robust model predictive control approach 36

Optimal tracking cooperative control for multi-agent systems...

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第36届中国控制会议

作者： Bohui Wang Weisheng Chen Jingcheng Wang Bin Zhang Zhengqiang Zhang Hai Lin Bin Ma the School of Aerospace Science and Technology Xidian University the Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China the Autonomous Systems and Intelligent Control international Joint Research Center Xian Technological University the Department of Electrical Engineering University of South Carolina the with the School of Engineering Qufu Normal University

ISBN: (纸本)9781538629185

This paper addresses the optimized tracking cooperative control problem for multi-agent systems with periodic sampling and directed communication topology via robust model predictive control *** proposed optimized tracking cooperative control strategy relaxes the assumptions in existing works that the control gain and the local input must be continuous and the states information exchange has no recourse *** the conditions of the optimized consensus and the communication cost being satisfied,the tracking cooperative control law with bounded parameters is developed based on the periodic *** shows that if the sampling condition is satisfied,the multi-agent systems will reach the optimized *** results are provided to verify the proposed approach.

关键词： Index Terms-multi-agent systems tracking cooperative control periodic sampling optimized consensus robust model predictive control

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