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

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

引用

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

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

引用

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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Analysis and Maximum Efficiency Design for Wireless Power Transfer systems

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

引用

第37届中国控制会议

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

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： Wireless Power Transfer Magnetic Resonance Efficiency Maximization

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EEG emotion recognition based on LDA and PSO-SVM 5

EEG emotion recognition based on LDA and PSO-SVM

引用

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

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

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第37届中国控制会议

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

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 neuralnetwork 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： Grid-connected converter RNN controller LM plus FATT algorithm Simulation

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Stability Analysis and Bifurcation control of a Delayed Fractional Order GRNs Model

Stability Analysis and Bifurcation Control of a Delayed Frac...

引用

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

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

引用

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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Consensus of discrete-time second-order multi-agent systems with delayed and noisy measurements under balanced digraphs 29

Consensus of discrete-time second-order multi-agent systems ...

引用

第29届中国控制与决策会议

作者： Xiaofeng Zong Tao Li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mathematics East China Normal University Shanghai Key Laboratory of Power Station Automation Technology

ISBN: (纸本)9781509046584

This paper studies mean square and almost sure consensus of discrete-time second-order multi-agent systems with time-delays and multiplicative noises in the information exchange with *** using the stochastic stability theorem of discrete-time stochastic delay systems,we find sufficient conditions for mean square and almost sure consensus explicitly related to the network and control *** is shown that if the network graph is balanced and strongly connected,then the weighted-average type control protocol can be properly designed to ensure mean square and almost sure consensus for any given time-delays and noise intensity coefficients.

关键词： Second-order multi-agent system Multiplicative noise Time-delay Consensus

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Analysis and Maximum Efficiency Design for Wireless Power Transfer systems

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

引用

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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Street Object Detection Based on Faster R-CNN

Street Object Detection Based on Faster R-CNN

引用

Chinese control Conference

作者： Wendi Cai Jiadie Li Zhongzhao Xie Tao Zhao Kang Lu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. china The Library of Wuhan University of Technology Wuhan P. R. China

With the increased number of traffic accidents, the research and development of smart cars have been promoted. The detection of street objects has become one of the important research topics. Generic Model detection algorithm based on Convolution Neural Network(CNN) need to design the training model, while the training and testing of the model will take a lot of time. Transfer Learning is used to fine-tune the pre-trained models, using the Image task datasets of COCO, transferring a generic deep learning model to specific one with different weights and outputs. Furthermore, the CNN structure is adjusted to improve overall performance, and the street environment is trained to the special scene. We compare the results of experiments, and the results showed that the network which is fine-tuned is effective.

关键词： Object detection Computer vision Training Proposals Machine learning Automobiles Convolution

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