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第37届中国控制会议

作者： Feng Liu Jie Ren Guang Ling Longsheng Wei Shiqi Zheng Hua Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Science Wuhan University of Technology Department of Mechanical Engineering Boston University

In this paper, a fractional order genetic regulatory network system（GRNs） with delay is considered. Firstly, the stability is investigated and the conditions of the existence for Hopf bifurcation are attained by analyzing it’s characteristic equation. Then combining the analysis we can derive that the fractional order GRNs will generate Hopf bifurcation as the GRNs with specific parameter values. A fractional PD controller can be used to control the bifurcation behaviors of the delayed fractional order GRNs. Finally, some numerical examples are exploited to illustrate the validity of theoretical analysis.

关键词： Stability Hopf bifurcation fractional order GRNs control

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A threshold segmentation method for non-uniform illumination image based on brightness equalization

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IOP Conference Series: Materials Science and Engineering 2019年第5期569卷

作者： Hui Guo Peng Chen Shun Huang Cong Hu Lijun Zhang School of Automation China University of Geosciences Wuhan 430074 China Hubei key laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan 430074 China

In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, an image threshold segmentation method is proposed for non-uniform illumination images. First, the brightness of different regions in the image is compensated to make the brightness background of the whole image consistent. Second, the gradation histogram of the processed image is obtained and simulated into Gaussian distribution curve, then the inflection points of the curve are calculated. Finally, the two inflection points are set as thresholds to segment the image after brightness equalization. This method eliminates the influence of non-uniform illumination to a certain extent and gets a better segmentation effect. Experiments were carried out on images containing several different types of non-uniform illumination. The results demonstrate that the proposed method outperforms the compared enhancement algorithms in threshold segmentation.

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Valve Stiction Compensation Based on Equivalent-Input-Disturbance Approach 29

Valve Stiction Compensation Based on Equivalent-Input-Distur...

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第29届中国控制与决策会议

作者： Qi Lei Xi Lei Min Wu School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781509046584

The presence of stiction in a control valve causes loop oscillation,and limits the control loop *** address this problem,the paper proposes a method based on equivalent-input-disturbance（EID） to control valve *** this method,a classic two-parameter stiction model is ***,an EID estimator is utilized to estimate the effects of valve stiction in control *** the controller is designed in the spirit of repetitive *** simulation control results are compared with the traditional *** results demonstrate that the proposed EID method can effectively improve the control performance of valve stiction and eliminate the stiction-induced oscillations.

关键词： Valve Stiction EID Repetitive control Compensation

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Image retrieval based on convolutional neural network and linear discriminate analysis

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IOP Conference Series: Materials Science and Engineering 2019年第5期569卷

作者： Wei Xia Cong Hu Xianghui Cheng Peng Chen Xing Jin School of Automation China University of Geosciences Wuhan 430074 China Hubei key laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan 430074 China

Image retrieval is a hot research topic in the field of computer vision image processing, and the user queries the image database for similar images and produces a list of recommendations. The paper firstly sets forth the research status of image retrieval, then the convolution neural network is briefly introduced. Due to the traditional image retrieval and recommendation system use manual extraction of image features is relatively cumbersome, and the retrieval accuracy is not high research status, the paper proposes an image retrieval method based on the improved convolutional neural network and linear discriminate analysis. Caltech256 and CIFAR-10 datasets were trained using the model in this paper, experimental, results show that the proposed method can effectively improve the performance of retrieval.

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Multi objective optimization based on SPEA for the microgrid energy dispatch

Multi objective optimization based on SPEA for the microgrid...

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Chinese control Conference

作者： Xiaomin Wu Weihua Cao Dianhong Wang Min Ding Hubei KEY Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

Microgrid provides an effective technical approach for distributed generation system connected to the power grid. There are renewable sources such as wind power, photovoltaic in the microgrid, which the power volatility of distributed generation limits the effective scheduling and real-time performance of microgrid. Energy storage device is used to stabilize the volatility of distributed generation, make sure the feasibility of distributed generation optimal scheduling. Microgrid optimizes scheduling the energy allocation of various types of distributed generation in technology, economy, environment and other aspects. In order to solutio the multi objective optimization of microgrid energy allocation, a Strength Pareto Evolutionary Algorithm based optimal method was proposed. Finally, the correctness and feasibility of the proposed method were verified through the simulation.

关键词： Microgrids Distributed power generation Optimization Batteries Solar power generation Generators

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Transfer learning from generic model to specific model for street object detection 5

Transfer learning from generic model to specific model for s...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Liu, Wei Chen, Shu Liu, Zhen-Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Japan

High accurate rate of street objects detection is significant to realize intelligent vehicles. Algorithms based on Convolution Neural Network (CNN) have already shown their reasonable performance on general object detection. For example SSD and YOLO can detection wide variety of objects on 2D images in real time, but the performance is not good enough on street objects detection especially on complex urban street environment. In this paper, instead of proposing and training a new CNN model, we use transfer learning methods to learn from generic CNN model to our specific model to achieve good performance. The transfer learning methods include fine-tuning the pretrained CNN model with self-made dataset and adjusting CNN model structure. We analyze transfer learning results on fine-tuning Single shot multibox detector (SSD) with self-made datasets. The experimental results based on transfer learning method show that the proposed method is effective.

关键词： Object detection

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EEG emotion recognition based on LDA and PSO-SVM 5

EEG emotion recognition based on LDA and PSO-SVM

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Liu, Zhen-Tao Xie, Qiao Cao, Wei-Hua Li, Dan-Yun Zhang, Ri Ding, Xue-Wen School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Japan

Compared with speech, facial expression, and body languages, Electroencephalogram (EEG) can reflect the inner activity of brain, by which the emotion can be recognized objectively and naturally. In this paper, an EEG emotion recognition system is proposed in which EEG signals of 6 channels are detected from Frontal Lobe and Temporal Lobe, and then the time-domain features of statistics features and frequency-domain features of spectrum centroid (SC) are extracted. To remove the redundant feature, Linear Discriminant Analysis (LDA) is used to reduce the dimension of feature. In addition, an improved classifier based on PSO-SVM is applied to classify the emotional states in the Valance-Arousal emotion model, respectively, which are defined as High-Valance (HV) and Low-Valance (LV) on the Valance dimension and High-Arousal (HA) and Low-Arousal (LA) on the Arousal dimension. EEG emotion recognition experiment on DEAP dataset is performed, from which the results show that the proposed method obtains the accuracies of 73.33% on Valance dimension and 72.78% on Arousal dimension, which are higher than those of some state-of-the art works.

关键词： Emotion Recognition

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Speaker-independent speech emotion recognition based on genetic algorithm feature selection approach 5

Speaker-independent speech emotion recognition based on gene...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Mao, Jun-Wei He, Yong Liu, Zhen-Tao Cao, Wei-Hua Xu, Jian-Ping School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems China

For speech emotion recognition (SER), emotional feature set with high dimension may produce redundant features and influence the recognition rate. To solve this problem, feature selection of speaker-independent speech based on genetic algorithm (GA) is proposed, which can obtain optimal feature subset. And a four-level emotional classification method based on support vector machine (SVM) is proposed according to the confusion degree among different emotional categories. A framework of speaker-independent SER is presented and the classification experiments based on proposed methods by using Chinese speech database from institute of automation of Chinese academy of sciences (CASIA) are performed, where the speaker-independent features selected by the proposed feature selection method and Spearman correlation analysis are used for emotion recognition, respectively. The experimental results show that the proposal achieved 77.6% recognition rate on average, which is about 1.2% higher than other recognition methods. By proposal, it would be efficient to distinguish the emotional states of different speakers from speech.

关键词： Genetic algorithms

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Current controller Based on Recurrent Neural Network for Grid-Connected Converter

Current Controller Based on Recurrent Neural Network for Gri...

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Chinese control Conference (CCC)

作者： Xuefen Wang Hongbin Wang Qingyi Wang Min Ding Quan Yin Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China State Grid Corporation of China Wuhan China School of Automation Huazhong University of science and technology Wuhan China

Three-phase grid-connected converters are widely used in renewable and electric power system applications. Due to system nonlinearity and time-variant characteristic, there are limitations in standard decoupled d-q vector control mechanism. To mitigate these limitations, a RNN vector controller trained with Levenberg-Marquardt and FATT(Forward accumulation through time) algorithm is designed. The simulation is researched by using MATLAB software, and the results show that training neural-network algorithm is effective and the system using RNN vector control method outperforms the system using conventional PI control method under low sampling rate conditions.

关键词： Mathematical model Training Artificial neural networks Recurrent neural networks Voltage control Convergence

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Analysis and Maximum Efficiency Design for Wireless Power Transfer Systems

Analysis and Maximum Efficiency Design for Wireless Power Tr...

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Chinese control Conference

作者： Bing Cao Hongbin Wang Qingyi Wang Min Ding Quan Yin Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China State Grid Corporation of China Wuhan China School of Automation Huazhong University of science and technology Wuhan China

How to stabilize the output voltage while ensuring the maximum charging efficiency of the system is a problem faced by the development of wireless power transfer(WPT). Especially in the dynamic environment, the change of system coupling coefficient or load resistance will have a huge impact on the system. In this paper, a two-stage DC-DC converter control mode is used to control the system with the goal of dynamic charging demand. Among them, the system achieves impedance matching through the receiver DC-DC converter to ensure the transmission efficiency of the system, and in order to match the impedance, the voltage and current information in the coil is used to calculate the coupling coefficient, then, the coupling coefficient can be used to achieve maximum efficiency. The system output voltage is stabilized by using the transmitter DC-DC converter. The simulation experiment shows that the control mode can stabilize the output voltage well, and is more efficient than the single receiver closed loop control(SRCLP) system.

关键词： Resistance Couplings DC-DC power converters control systems Voltage control Receivers Frequency control

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