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Adaptive critic design based dynamic optimal power flow controller for a smart grid

Adaptive critic design based dynamic optimal power flow cont...

引用

IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Jiaqi Liang Ronald G. Harley Ganesh K. Venayagamoorthy School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla MO USA

An adaptive critic design (ACD) based dynamic optimal power flow control (DOPFC) is proposed in this paper as a solution to the smart grid operation in a high short-term uncertainty and variability environment. With the increasing penetration of intermittent renewable generation, power system stability and security need to be ensured dynamically as the system operating condition continuously changes. The proposed DOPFC dynamically tracks the power system optimal operating point by continuously adjusting the steady-state set points from the traditional OPF algorithms. The ACD technique, specifically the dual heuristic dynamic programming (DHP), is used to provide nonlinear optimal control, where the control objective is formulated explicitly to incorporate system operation economy, stability and security considerations. A 12 bus test power system is used to demonstrate the development and effectiveness of the proposed ACD-based DOPFC using recurrent neural networks.

关键词： Power system dynamics Recurrent neural networks Generators Power system stability Automatic generation control Training

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Fast double-parallel image processing based on FPGA

Fast double-parallel image processing based on FPGA

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IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： Ye Li Qingming Yao Bin Tian Wencong Xu State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China School of Mechanical Electrical and Information Engineering Shandong University Weihai China

Due to FPGA's flexibility and parallelism, it is popular for accelerating image processing. In this paper, a double-parallel architecture based on FPGA has been exploited to speed up median filter and edge detection tasks, which are essential steps during image processing. The double-parallel scheme includes an image-level parallel and an operation-level parallel. The image-level parallel is a high-level parallel which divides one image into different parts and processes them concurrently. The operation-level parallel, which is embedded in each image-level parallel thread, fully explores every parallel part inside the concrete algorithms. The corresponding design is based on a DE2 Development Board which contains a CYCLONE II FPGA device. Meanwhile, the same task has also been implemented on PC and DSP for performance comparison. Despite the fact that operating frequencies of used PC and DSP are much higher than FPGA's, FPGA costs less time per computed image than both of them. By taking advantage of the double-parallel technique, the speed/frequency ratio of FPGA is 202 times faster than PC and 147 times faster than DSP. Finally, a detailed discussion about different platforms is conducted, which analyzes advantages and disadvantages of used computing platforms. This paper reveals that the proposed double-parallel scheme can dramatically speed up image processing methods even on a low-cost FPGA platform with low frequency and limited resources, which is very meaningful for practical applications.

关键词： Image edge detection Field programmable gate arrays Digital signal processing Hardware Kernel Detectors

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Effective Supervised Classification of fMRI Activation Maps between Populations by Spatial Descriptors

Effective Supervised Classification of fMRI Activation Maps ...

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Iranian Machine Vision and Image Processing (MVIP)

作者： Shaghayegh Eshaghian Gholam-Ali Hossein-Zadeh Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA

The major obstacle in discrimination between different groups of subjects in a common cognitive state, by functional Magnetic Resonance Imaging (fMRI), has been the high inter- subject functional and anatomical variability in the spatial patterns of brain activity. To overcome this, we have used two types of spatial descriptors that characterize the brain regions of interest (ROIs) involved in the cognitive tasks. They include, firstly three-dimensional invariant moment descriptors (3-DMIs), and secondly k-dimensional feature vectors based on concentric spheres. Both types of descriptors are applied to analyze the spatial patterns of cognitive activity of a challenging task and then to classify them across two different subject groups. SVM classifiers along with sequential floating forward feature selection technique are applied to the extracted descriptors of each ROI across the subjects. Our method is applied to experimental fMRI data with the aim of discriminating mental status of heroin IV (Intravenous) abusers and from of those in control subjects in a visual cue task which can induce drug craving. Our results demonstrate that 3-D texture of activation maps provide a good discrimination (with high accuracy) between healthy and addict group.

关键词： Feature extraction Accuracy Drugs Brain Support vector machine classification Visualization Humans

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Improved particle swarm optimization and applications to Hidden Markov Model and Ackley function

Improved particle swarm optimization and applications to Hid...

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IEEE International Conference on Computational Intelligence for Measurement systems and Applications (CIMSA)

作者： Saeed Motiian Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA

Particle Swarm Optimization (PSO) is an algorithm based on social intelligence, utilized in many fields of optimization. In applications like speech recognition, due to existence of high dimensional matrices, the speed of standard PSO is very low. In addition, PSO may be trapped in a local optimum. In this paper, we introduce a novel algorithm that is faster and generates superior results than the standard PSO. Also, the probability of being trapped in a local optimum is decreased. To illustrate advantages of the proposed algorithm, we use it to train a Hidden Markov Model (HMM) and find the minimum of the Ackley function.

关键词： Hidden Markov models Training Particle swarm optimization Speech processing Educational institutions Algorithm design and analysis Optimization

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Sport Video Classification Using an Ensemble Classifier

Sport Video Classification Using an Ensemble Classifier

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Iranian Machine Vision and Image Processing (MVIP)

作者： Mohamad Hoseyn Sigari Samaneh Abbasi Sureshjani Hamid Soltanian-Zadeh Control & Intelligent Processing Center of Excellence (CIPCE) School of Electrical & Computer Engineering College of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA

Sport video classification is an application of video analysis which can be useful in video indexing and retrieval. In this article, a new method for sport video classification using ensemble classifier is proposed. The proposed method uses 6 features: 3 dominant colors, dominant gray level, cut rate and motion rate. These features are classified by 4 simple classifiers in an ensemble classifier: Nearest Neighbor (NN), Linear Discriminant Analysis (LDA), Decision Tree (DT) and Probabilistic Neural Network (PNN). To combine the output of simple classifiers and make final decision, weighted majority vote is used while the weight of each simple classifier is equal to corresponding correct classification rate (CCR). Experimental result shows that the CCR of proposed system is 78.8%. In this experiment, 104 clips in 7 different sport classes are used: football, basketball, tennis, swimming, futsal, ski and box.

关键词： Feature extraction Color Image color analysis Classification algorithms Accuracy Artificial neural networks Histograms

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Universal Steganalysis Based on Local Prediction Error in Wavelet Domain

Universal Steganalysis Based on Local Prediction Error in Wa...

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International Conference on intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Anahita Shojaei-Hashemi Mostafa Mehdipour-Ghazi Shahrokh Ghaemmaghami Hamid Soltanian-Zadeh School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electronics Research Institute Sharif University of Technology Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes.

关键词： Equations Mathematical model Payloads Transform coding Correlation Educational institutions Reliability

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Distributed Output Regulation of Uncertain and Switching Multi-Agent systems via Internal Model Design

Distributed Output Regulation of Uncertain and Switching Mul...

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2011 China control and Decision Conference(2011中国控制与决策会议 CCDC)

作者： Xiaoli Wang Yiguang Hong Zhong-Ping Jiang School of Information Science and Engineering Harbin Institute of Technology atWeihaiWeihai 264209 Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy o Department of Electrical and Computer Engineering Polytechnic Institute of New York University Six

In this paper, the distributed robust output regulation problem of linear multi-agent systems (MAS) is considered. The driving force from the active leaders or the environmental disturbances is formulated as an input of an exogenous system (or exosystem) of the considered multi-agent networks. A systematic distributed design approach is proposed to handle output regulation via dynamic output feedback with the help of canonical internal model (IM). With common solutions of regulator equations and Lyapunov functions, the distributed robust output regulation with switching interconnection topology is designed to achieve collective aims.

关键词： Output regulation Multi-agent systems Internal Model Switching Topology

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Wavelet autoregressive forecasting of climatic parameters for photovoltaic systems

Wavelet autoregressive forecasting of climatic parameters fo...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Chokri Ben Salah Anouar Ben Mabrouk Mohamed Ouali Research Unit on Intelligent Control Optimization design & optimization of complex Systems (ICOS) Department of Electrical Engineering National School of Engineers of Sfax Sfax Tunisia Department of Computer Sciences Higher Institute for Applied Sciences and Technology HIAST Sousse Tunisia Department of Electrical Engineering National School of Engineers of Sfax Sfax Tunisia

ISBN: (纸本)9781457704130

In this paper wavelet decomposition is combined with autoregressive models to analyze and predict climate time series such as solar radiation and photovoltaic cell temperature. The method is tested on climate parameters for analysis, and solar radiation and cell temperature for prediction. The work effectiveness is evaluated by the prediction of the electric energy produced by a 100 Wp photovoltaic panel. Finally, the performance of predictor is measured by standardized error.

关键词： Mathematical model Temperature measurement Time series analysis Predictive models Solar radiation Wavelet analysis Photovoltaic systems

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A delay system method to design of event-triggered control of networked control systems

A delay system method to design of event-triggered control o...

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IEEE Conference on Decision and control

作者： Dong Yue Engang Tian Qing-Long Han Department of Control Science and Engineering and the Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Hubei 430074 China School of Electrical and Automation Engineering Nanjing Normal University 78 Bancang Street Nanjing 210042 China Center for Intelligent and Networked Systems and the School of Information and Communication Technology Central Queensland University Rockhampton Qld 4702 Australia

ISBN: (纸本)9781612848006

The event-triggered H_(infinity) control design is investigated for networked control systems with uncertainties and transmission delays. A novel event-triggering scheme is proposed, which has some advantages over traditional ones with a continuous detector. Considering the effect of the transmission delay, a delay system model for the analysis is firstly constructed. Then, based on the model and Lyapunov functional method, criteria for the stability with an H_(infinity) norm bound and criteria for the co-design of both the feedback gain and the trigger parameters are derived. In order to solve the feedback gain and the trigger parameters, the linear matrix inequality technique is employed. From the simulation example, it can be concluded that the proposed event-triggering scheme is superior to some other event-triggering schemes in some existing literature.

关键词： feedback gain Networked control systems Event trigger Delay systems Scheme Co-design control systems design control

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Effect of Different Diffusion Maps on Registration Results

Effect of Different Diffusion Maps on Registration Results

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Iranian Machine Vision and Image Processing (MVIP)

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory (BiSIPL) Sharif University of Technology Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper, we compare registration results obtained using different diffusion maps extracted from diffusion tensor imaging (DTI). Fractional Anisotropy (FA) and Ellipsoidal Area Ratio (EAR) are two diffusion maps (indices) that may be used for image registration. First, we use FA maps to find deformation matrix and register diffusion weighted images. Then, we use EAR maps and finally we use both of FA and EAR maps to register diffusion weighted images. The difference between FA values before deformation and after registration using the FA alone or EAR alone has a median of 0.57 and using both of them has a median of 0.29. Therefore, the results of registration using both of the FA and EAR indices are superior to those obtained using only one of them alone.

关键词： Ear Diffusion tensor imaging Tensile stress Registers Eigenvalues and eigenfunctions Anisotropic magnetoresistance Image registration

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