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Fast Multi-Operator Image Resizing and Evaluation

Journal of computer Science & Technology 2012年第1期27卷 121-134页

作者： Wei-Ming Dong Guan-Bo Bao Xiao-Peng Zhang Jean-Claude Paul Sino-French Laboratory for Computer Science Automation and Applied Mathematics/National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China National Institute for Research in Computer Science and Control Domaine de Voluceau Rocquencourt Le Chesnay 78153France

Current multi-operator image resizing methods succeed in generating impressive results by using image similarity measure to guide the resizing process. An optimal operation path is found in the resizing space. However, their slow resizing speed caused by inefficient computation strategy of the bidirectional patch matching becomes a drawback in practical use. In this paper, we present a novel method to address this problem. By combining seam carving with scaling and cropping, our method can realize content-aware image resizing very fast. We define cost functions combing image energy and dominant color descriptor for all the operators to evaluate the damage to both local image content and global visual effect. Therefore our algorithm can automatically find an optimal sequence of operations to resize the image by using dynamic programming or greedy algorithm. We also extend our algorithm to indirect image resizing which can protect the aspect ratio of the dominant object in an image.

关键词： image resizing multi-operator operator cost indirect resizing

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A Sensorless Method based on Zero-sequence Back-EMF for Five-phase Open-end Winding PMSM with Deadtime Compensation

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IEEE Transactions on Energy Conversion 2025年

作者： Jiang, Chunyang Wang, Yingjie Liu, Hongchen Wheeler, Pat Bao, Danyang Northeast Forestry University College of Computer and Control Engineering Harbin 150001 China Harbin Institute of Technology School of Electrical Engineering and Automation Harbin 150001 China University of Nottingham Department of Electrical and Electronics Engineering Nottingham NG7 2RD United Kingdom Shenzhen Polytechnic University School of Mechanical and Electrical Engineering Shenzhen 518000 China

This paper proposes a sensorless method using the zero-sequence back electromotive force (ZSB-EMF) for five-phase open-end winding permanent magnet synchronous machine (OEW-PMSM) with common dc bus. The output of the zero-sequence controller, which is applied to suppress the zero-sequence current (ZSC), is used to reconstruct the ZSB-EMF. Then the position of the rotor is extracted from the output signal of the zero-sequence controller by single phase locked loop. A compensation of the deadtime is proposed to eliminate the negative effect for the position estimation and increase the effective modulation index. The proposed method needs no parameters of the motor, like the resistance, d-q inductance, which are vulnerable and might affect the accuracy of the estimation for the conventional sensorless methods based on the ZSB-EMF. It is easy to implement and the resistance network and complex calculation of conventional methods are also avoided. Experimental results on the five-phase open-end winding PMSM drive system are shown to validate the proposed sensorless method. © 1986-2012 IEEE.

关键词： Common dc Bus Deadtime Compensation Five-phase Open-end Winding Permanent Magnet Synchronous Machine Sensorless method

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LDNet-RUL: Lightweight Deformable Neural Network for Remaining Useful Life Prognostics of Lithium-ion Batteries

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IEEE Transactions on Power Electronics 2025年

作者： Wu, Xiankui Li, Penghua Deng, Zhongwei Liu, Zhitao Kurboniyon, Mekhrdod S. Xiang, Sheng Yin, Gang Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing400065 China Chongqing University of Posts and Telecommunications School of Automation Chongqing400065 China Chongqing University of Science and Technology School of Computer Science and Engineering Chongqing401331 China University of Electronic Science and Technology School of Mechanical and Electrical Engineering Chengdu611731 China Zhejiang University Institute of Cyber-Systems and Control Zhejiang 310058 China National Academy of Sciences of Tajikistan Center of Innovative Development of Science and New Technologies Dushanbe734025 Tajikistan Chongqing University College of Resource and Safety Engineering Chongqing400044 China

Deep neural networks (DNNs)-based battery remaining useful life (RUL) prognostics models suffer from high computational costs, long inference times, and a tendency to overfit, posing significant challenges for deployment on memory-constrained edge devices. To address this, LDNet-RUL, a lightweight yet high-performance model, is proposed for lithiumion battery lifetime prognostics. Specifically, a deformable depthwise convolution unit is designed that efficiently adapts to variations in input features with relatively low computational cost, which leverages fewer parameters and an adaptive receptive field to capture battery degradation dynamics. A multi-scale feature extraction method is introduced to extract degradation features from both short-term and long-term data during the battery charging process, which makes the method applicable to various battery charging protocols. To address overfitting and accelerate model inference, an adaptive channel selector, an adaptive residual connector, and a progressive dimensionalitygrouped bottleneck filter are incorporated to refine feature selection and reduce the model's complexity, boosting the model's overall performance. Experiments on vehicle lithium-ion battery datasets demonstrate that LDNet-RUL achieves state-of-the-art (SOTA) performance, with average RMSE of 0.23 and Score of 0.49. The model is lightweight, with only 7.92K parameters, achieves inference times of 3.94ms on GPU and CPU, and 5.39ms on the NVIDIA Jetson TX2. © 1986-2012 IEEE.

关键词： Convolution

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Distributed Online Convex Optimization with Time-Varying Constraints: Tighter Cumulative Constraint Violation Bounds under Slater's Condition

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IEEE Transactions on Automatic control 2025年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology China Ministry of Education Frontiers Science Center for Intelligent Autonomous Systems China Massachusetts Institute of Technology Lab for Information & Decision Systems CambridgeMA02139 United States Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Nanyang Technological University School of Electrical and Electronic Engineering 50 Nanyang Avenue 639798 Singapore Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with time-varying constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize static network regret and network cumulative constraint violation. A novel distributed online algorithm with a vanishing stepsize is proposed and it achieves an O(Tmax {c,1-c}) static network regret bound and an O(T1-c/2) network cumulative constraint violation bound, where T is the number of rounds and c∈ (0,1) is a user-defined trade-off parameter. When Slater's condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T1-c). Moreover, if the loss functions are strongly convex, then static network regret bound is reduced to O(log (T)), and the network cumulative constraint violation bound is reduced to O(√log (T)T) and O(log (T)) without and with Slater's condition, respectively. To the best of our knowledge, this paper is the first to achieve tighter (network) cumulative constraint violation bounds for (distributed) online convex optimization with time-varying constraints under Slater's condition. Finally, the theoretical results are verified through numerical simulations. © 1963-2012 IEEE.

关键词： Convex optimization

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Model reduction and identification of nonlinear reactive sputter processes

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IFAC-PapersOnLine 2017年第1期50卷 13728-13734页

作者： Woelfel, Christian Awakowicz, Peter Lunze, Jan Institute of Automation and Computer Control Ruhr-University Bochum Germany Institute for Electrical Engineering and Plasma Technology Ruhr-University Bochum Germany

A model for nonlinear reactive sputter processes is developed based on a system theoretic analysis. Hence, a physical model from the fields of thin film science and vacuum science is analysed and reduced in order to describe the input/output behavior of the process by a nonlinear Abel differential equation. Hereby the input/output behavior is related to a supercritical Pitchfork-bifurcation. The parameter identification of the reduced model is discussed and an experiment for model validation is presented. The experiment shows high conformity between the reduced model and the measured input/output behavior of the process. The reduced model can be used as basis for control design for process stabilization. © 2017

关键词： Reactive sputtering Differential equations Nonlinear equations Nonlinear systems Input/output behaviors Model reduction Model validation Pitch fork bifurcations Process identification Process stabilization Sputter process Theoretic analysis

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Neural-Network-Based Terminal Sliding Mode control for Frequency Stabilization of Renewable Power Systems

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IEEE/CAA Journal of Automatica Sinica 2018年第3期5卷 706-717页

作者： Dianwei Qian Guoliang Fan School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Institute of Automation Chinese Academy of Sciences Beijing 100190 China

This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.

关键词： Generation rate constraint(GRC) load frequency control(LFC) radial basis function neural networks(RBF NNs) renewable power system terminal sliding mode control(T-SMC)

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Learning impedance control of robots with enhanced transient and steady-state control performances

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Science China(Information Sciences) 2020年第9期63卷 204-216页

作者： Tairen SUN Long CHENG Liang PENG Zengguang HOU Yongping PAN State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Data and Computer Science Sun Yat-sen University

This study proposes a learning impedance controller comprising a proportional feedback control term, a composite-learning-based uncertainty estimation term, and a robot-environment interaction control term. The impedance control problem is converted into a particular reference-trajectory tracking problem based on a generated reference trajectory. The proposed controller ensures the exponential convergence of the auxiliary tracking error and the uncertainty estimation error. The interaction control term improves the transient control performance through suppression/encouragement of the incorrect/correct robot *** composite-learning update law enhances the transient and steady-state control performances based on the exponential convergence of the uncertainty estimation error and auxiliary tracking error. Finally, the effectiveness and advantages of the proposed impedance controller are validated by theoretical analysis and simulations on a parallel robot.

关键词： robot adaptive control neural network impedance control parameter convergence

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Decentralised diagnosis of automata networks

Decentralised diagnosis of automata networks

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作者： Neidig, Jörg Lunze, Jan Institute of Automation and Computer Control Ruhr-Universiẗat Bochum Germany

ISBN: (纸本)008045108X

Automata-theoretic models have been used successfully in modelbased process supervision and diagnosis. From a practical viewpoint, their main drawback is their complexity, which increases fast with the size of the original discrete-event system. This complexity can be reduced by compositional modelling resulting in an automata network. The reduced complexity of the network leads to a complexity reduction of the diagnostic algorithm, as the fault diagnosis can be performed in a decentralised way. The paper develops such a diagnostic method for nondeterministic and stochastic automata networks. Copyright © 2005 IFAC.

关键词： Automata theory

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control design for nondeterministic Input/Output automata

Control design for nondeterministic Input/Output automata

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作者： Nke, Y. Lunze, J. Ruhr-University Bochum Institute of Automation and Computer Control Germany

ISBN: (纸本)9783902661937

This paper presents a control design approach for Input/Output (I/O) automata. The main contribution consists of an explicit description of the control design procedure, which leads to an implementation-friendly architecture. Moreover, the concepts of well-posedness of the control loop and controllability are investigated. The level control of a chemical process is used as a case study for demonstration purposes. © 2011 IFAC.

关键词： Discrete event simulation

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A design method for hybrid event-based control systems

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IFAC-PapersOnLine 2015年第27期48卷 135-140页

作者： Noesselt, Tobias Schultalbers, Matthias Lunze, Jan IAV GmbH Gifhorn Germany Ruhr-University Bochum Institute of Automation and Computer Control BochumD-44780 Germany

This paper investigates control systems, where the controller influences the plant through two control input signals with different characteristics. A continuous control input is used to attenuate disturbances and force the plant to follow a reference trajectory, whereas the operation point of the plant is adjusted by an event-based component of the controller, determining a discrete-valued input signal. Systems of this type are called hybrid event-based control (HEBC) systems. They have typical characteristics of hybrid dynamical systems, because the behaviour of the control loop includes state jumps and switches of the dynamics. In applications, these hybrid phenomena have been neglected and the controllers have been tuned by heuristic rules. To open the way for a systematic control design, this paper clarifies the structure of HEBC systems and introduces a specific model. Based on the model, a design method is proposed for a special class of hybrid event-based controllers, that mimic the behaviour of a purely continuous reference system. The performance of the closed-loop system is investigated by establishing an upper bound on the deviation between the closed loop and the continuous reference system. An application example illustrates the design method and the behaviour of hybrid event-based control loops. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： controllers Closed loop systems control systems Design Hybrid systems Application examples control design Discrete valued input Event based control Event based control system Hybrid dynamical systems Performance analysis Reference trajectories

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