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State-of-Charge Dependent Battery Model Identification Using Gaussian Process Regression

IFAC-PapersOnLine 2021年第3期54卷 647-652页

作者： Kesen Fan Yiming Wan Key Laboratory of Image Processing and Intelligent Control Ministry of Education China and School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China

This paper investigates the parameter identification of a state-of-charge dependent equivalent circuit model (ECM) for Lithium-ion batteries. Different from most existing ECM identification methods, we focus on identifying the functional relations between ECM parameters and state-of-charge (SOC). By transforming the ECM into an ARX model, a Gaussian process regression (GPR) approach is proposed, without using parametric functions to describe the SOC dependence of ARX coefficients. The proposed approach derives the posterior distributions of ECM parameters, thus is capable to quantify the estimation uncertainties. Another advantage lies in the flexibility of incorporating the knowledge of batteries into the prior distributions used in GPR, which enhances the estimation performance in the presence of noises. The effectiveness of the proposed GPR approach is illustrated by simulation examples under both low and high noise levels.

关键词： Gaussian process regression non-parametric approach Lithium-ion battery equivalent circuit model state-of-charge dependent circuit parameter

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An Improved Non-local Means Filter for image Denoising

An Improved Non-local Means Filter for Image Denoising

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Yi Zhan Mingyue Ding Feng Xiao Xuming Zhang Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

This paper proposes a improved non-local means (NLM) filter for image denoising. Due to the drawback that the similarity is computed based on the noisy image, the traditional NLM method easily generates the artifacts in case of high-level noise. The proposed method first preprocesses the noisy image by Gaussian filter. Then, a moving window at each pixel of the noisy image is chosen as the search window, and meanwhile, a improved calculation method of spatial distance based on the preprocessed image is used for computing the similarity. Finally, combining the improved distance with search window based on the noisy image, the intensity of each pixel is restored as the traditional NLM method. The standard images are used to evaluate restoration performance of the proposed method. Additionally, the application on medical image denoising also demonstrates that our method is practical.

关键词： Noise measurement Noise Noise reduction image denoising image restoration Biomedical imaging image edge detection

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Adaptive synchronization of complex dynamical networks with time-varying delays

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Circuits, Systems, and Signal processing 2014年第4期33卷 1173-1188页

作者： Liu, Bo Wang, Xiaoling Su, Housheng Zhou, Hongtao Shi, Yuntao Li, Rong College of Science North China University of Technology Beijing 100144 China Department of Automation Shanghai Jiao Tong University Ministry of Education of China Shanghai 200240 China School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Beijing for Field-bus Technology and Automation North China University of Technology Beijing 100144 China Department of Applied Mathematical Sciences Shanghai Finance University Shanghai 201209 China

This paper addresses the problem of adaptive pinning synchronization of complex dynamical networks with nonlinear delayed intrinsic dynamics and time-varying delays. By introducing decentralized adaptive strategies to both the coupling strengths and the feedback gains, it is proved that the complex dynamical network can synchronize with the desired state for the bounded time-varying delays even when only one node is informed, without any global information of the underlying network. Finally, some numerical simulations are given to verify the main results and show the superiority of these self-designed adaptive strategies. © 2013 Springer Science+Business Media New York.

关键词： Complex networks

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3D TRUS image segmentation in prostate brachytherapy

3D TRUS image segmentation in prostate brachytherapy

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2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Ding, Mingyue Gardi, Lori Wei, Zhouping Fenster, Aaron Key Laboratory Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Imaging Research Laboratories Robarts Research Institute London Ont. N6A 5K8 Canada

ISBN: (纸本)0780387406

Brachytherapy is a minimally invasive interventional surgery used to treat prostate cancer. It is composed of three steps: dose pre-planning, implantation of radioactive seeds, and dose post-planning. In these procedures, it is crucial to determine the positions of needles and seeds, measure the volume of the prostate gland. Three-dimensional transrectal ultrasound (TRUS) imaging has been demonstrated to be a useful technique to perform such tasks. Compared to CT, MRI or X-ray imaging, US image suffers from low contrast, image speckle and shadows, making it challenging for segmentation of needles, the prostates and seeds in the 3D TRUS images. In this paper, we reviewed 3D TRUS image segmentation methods used in prostate brachytherapy including the segmentations of the needles, the prostate, as well as the seeds. Furthermore, some experimental results with agar phantom, turkey and chicken phantom, as well as the patient data are reported. © 2005 IEEE.

关键词： image segmentation

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Motion deblurring based on convolutional neural network 12th

Motion deblurring based on convolutional neural network

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12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Tan, Yunfei Zhang, Di Xu, Fei Zhang, Danyang Department of Physical Education Huazhong University of Science and Technology WuhanHubei430074 China Key Laboratory of Image Information Processing Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China JamaicaNY11451 United States

ISBN: (纸本)9789811071782

Object motion blur results when the object in the scene moves during the recording of a single exposure, either due to too rapid movement or long exposure, leaving streaks of the moving object in the image and thus degrading its quality. In this paper, we present a method to solve the object motion blur problem in images with clear static background. Specifically, we propose an object motion deblurring algorithm that uses a convolutional neural network with six convolutional layers to deblur the image. Taking advantages of the strong ability of feature learning in convolutional neural networks, our method can remove the blurring effect of fast-moving object while keeping the clear background untouched. It is well known that neural networks are best driven by large data sets and more data means more benefits for training convolutional neural networks;therefore, we generated training set of 144,000 images and test set of 32,400 images. Through carefully designed training process, our model learned the ability of deblurring the blurred object while keeping the clear background. The experiment results show that our approach can generate superior results to a representative image deblurring algorithm that treats the same blurred object and clear background. © Springer Nature Singapore Pte Ltd 2017.

关键词： image enhancement

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An Approach with Nested Partition for Resource-Constrained Project Scheduling Problem

An Approach with Nested Partition for Resource-Constrained P...

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2012 IEEE 19th International Conference on Industrial Engineering and Engineering Management(IE&EM 2012)

作者： Zhen-yuan Liu Wen-min Yu Institute of Systems Engineering Huazhong University of Science and Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control

A time-based nested partition （NP） approach is proposed to solve resource-constrained project scheduling problem （RCPSP） in this paper. In iteration, one activity is selected as the base point of which the finish time interval calculated by CPM is divided into two parts to form two subregions on the basis of the promising region of the last iteration. Then sampling is taken in both subregions and the surrounding region to determine the promising region and aggregate the other as the surrounding region of this iteration so that whether the backtracking or the moving operation being performed is determined. Double justification is also performed in iteration to improve the results. The results of numerical tests on PSPLIB show the effectiveness and time-efficient of the proposed NP method.

关键词： Double justification nested partition RCPSP sampling

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Edge preserving post-processing of wavelet compressed image

Edge preserving post-processing of wavelet compressed image

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International Conference on Signal processing Proceedings (ICSP)

作者： Yihua Tan Jinwen Tian Jian Liu State Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

This paper proposes a new post-processing algorithm with edge preserving. To control the granular and edge preserving in the process of post-processing, we introduce a new potential function. To avoid the non-linear obstacle, the object energy is converted with half-quadratic regularization. At last, the implementation of the algorithm is improved to speed up the computation. Experiments show our method can achieve the design object that effectively remove artifacts at the same time maintain the edges.

关键词： image coding Degradation image restoration Discrete cosine transforms Decoding Bit rate Quantization image reconstruction Laboratories image processing

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A Particle Filtering Algorithm for Tracking Moving Target under Clutter

A Particle Filtering Algorithm for Tracking Moving Target un...

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7th World Congress on intelligent control and Automation (WCICA 2008), vol.13

作者： Guocheng Liu Yongji Wang Chinese Education Ministry Key Laboratory for Image Processing & Intelligent Control Huazhong University of Science and Technology Wuhan China

On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So it can track the target with robustness. The proposed method was based on particle filter, integrated with color histogram in the measurement model, and the system model was second order autoregressive process. The algorithm took into account the latest observations and the tracked target can be rigid or non-rigid. Also the method can run in real-time. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.

关键词： Particle filter Visual tracking Color histogram

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Fault Detection of Lithium-Ion Batteries Subject to Probabilistic Parametric Uncertainties

Fault Detection of Lithium-Ion Batteries Subject to Probabil...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Yuhao Liu Yiming Wan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (数字)9781728106816

ISBN: (纸本)9781728106823

The fault detection task in lithium-ion battery management system (BMS) is critical to the safety and reliability of rechargeable and hybrid electric vehicles. To explicitly account for inevitable errors of battery model parameters, a robust fault detection method is proposed in this paper. The residual generator is established by exploiting an equivalent circuit model. The effect of uncertainties on the residual is parametrized as polynomial dependence on probabilistic uncertain parameters and noises. Then Gaussian mixtures are adopted to derive the residual distribution. To account for residual uncertainties in the detection decision, the weighted sum of distances from the generated residual to each Gaussian component of the residual distribution is proposed. Simulation results illustrate that our proposed method outperforms the conventional approach that does not consider parametric uncertainties.

关键词： Uncertainty Batteries Integrated circuit modeling Uncertain systems Voltage measurement Electronic countermeasures State of charge

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Adaptive fuzzy sliding mode control for pneumatic muscle actuator

Adaptive fuzzy sliding mode control for pneumatic muscle act...

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Chinese Automation Congress (CAC)

作者： Jin Qian Jian Huang Songhyok Ri Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China

In this paper, an adaptive fuzzy sliding mode control approach which combines fuzzy control with the sliding mode control, is applied for the tracking control of pneumatic muscle actuator (PMA). This actuator is widely used in the rehabilitation robots while hard to control due to its strong nonlinearity. The switching-type control term in the sliding mode control law is approximated by a fuzzy system. Based on Lyapunov theory, the stability of the closed-loop PMA system can be guaranteed. Both simulation and experimental studies were carried out to verify the proposed methods. The experiments were conducted on a real PMA system, which was connected with the xPC target system. The results demonstrate the validity of the PMA as well as the effectiveness of the control algorithm even there exist system uncertainties and external bounded disturbances.

关键词： Software Real-time systems Fuzzy control Robots Switches Mathematical model Sliding mode control

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