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第37届中国控制会议

作者： Xiao-Long Zhuang Wei-Hua Cao Yan Yuan Can Liu Yu-Sheng Guo School of Automation China University of Geosciences China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper proposes a coupling matrix element optimization method for microwave filters. The traditional method is more complex and does not directly optimize the filter coupling matrix elements. The firefly algorithm optimization method used in this paper directly optimizes the elements of the N + 2 order coupling matrix. Compared with the traditional method, it has better speed and optimization effect. First, the elements of the specific coupling matrix are introduced into the optimization algorithm to be executed, then the matrix is iterated through the set objective function. Finally, when the optimized data is within the allowable range, the optimization of the elements of the coupling matrix is stopped and optimization is performed. The resulting coupling matrix outputs the response. To prove the effectiveness of the proposed method, three methods were used to optimize the coupling matrix elements of the fourth-order filter and compare the final optimization results.

关键词： computer aided tuning coupling matrix ploynomial model extraction optimization

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Convolutional Neural Networks for Facial Expression Recognition with Few Training Samples

Convolutional Neural Networks for Facial Expression Recognit...

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Chinese control Conference

作者： Zhongzhao Xie Yongbo Li Xinmei Wang Wendi Cai Jing Rao Zhenzhu Liu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

Facial expression recognition (FER) plays an important role in human-machine interaction. An assistant robot having a close interaction with human being should be able to recognize human facial expression. FER is a non-trivial problem because each individual has his own way to reveal his emotion and the facial expressions of two different persons may not be totally identical. Hence, facial expression recognition is still a challenging problem in computer vision. In this work, we propose a simple solution for facial expression recognition that uses a combination of Convolutional Neural Network and specific image pre-processing steps. The experiments employed to evaluate our technique were carried out using two largely used public databases(CK+, JAFFE). A study of the impact of each image pre-processing operation in the accuracy rate is presented. The proposed method: achieves competitive results when compared with other facial expression recognition methods-97.85% of accuracy in the CK+ database-it is fast to train, and it allows for real time facial expression recognition with standard computers.

关键词： Training Face recognition Convolutional neural networks Neurons Convolution Feature extraction

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Unscented Kalman Filter for Nonlinear systems with One-step Randomly Delayed Measurements and Colored Measurement Noises

Unscented Kalman Filter for Nonlinear Systems with One-step ...

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Chinese control Conference (CCC)

作者： Xinmei Wang Zhenzhu Liu Leimin Wang Feng Liu Wei Liu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

In this paper, a new unscented Kalman filter (Unscented Kalman filter, UKF) for nonlinear system with both one-step randomly delayed measurements and colored measurement noises is proposed. Firstly, the first-order Markov sequence model is used to whiten colored noise, at the same time, an independent and identically distributed Bernoulli variable is used to model the delay of measurement data transmission, then the model of nonlinear one-step randomly time delay system with colored noise whitening is established. Secondly, filter recursion formula of UKF under the above model is proposed through unscented transformation (Unscented transformation, UT) to calculate the posterior mean and covariance of the nonlinear state based on the Bayesian filter framework. The proposed new UKF method can effectively deal with the issue that traditional UKF is failure under the condition of one-step randomly delayed measurements and colored measurement noises. The efficiency and superiority of the proposed method are illustrated in a numerical example for a target tracking problem.

关键词： Noise measurement Colored noise State estimation Delays Nonlinear systems Target tracking

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Image Jacobian Matrix Estimation based on Fuzzy Adaptive Robust Kalman Filter

Image Jacobian Matrix Estimation based on Fuzzy Adaptive Rob...

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Chinese control Conference

作者： Zhenzhu Liu Xinmei Wang Zhenjiang Feng Zhongzhao Xie Shuai Ke Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

Aiming at the problem of image Jacobian matrix estimation, this paper proposes a method to get the motion state estimation of the object feature point at the current time by using the combination of robust Kalman filter and fuzzy adaptive method from the image feature space, and the estimation of the image Jacobian matrix can be obtained. Firstly, an adaptive robust decorrelation Kalman filler algorithm with colored measurement noise is proposed by reconstructing process equation and measurement equation and combining the mathematical characteristics of the standard Kalman filter noise. Secondly, by monitoring if the ratio between theoretical residual and actual residual is near 1, the fuzzy inference system constantly adjust the weighted measurement noise covariance and recursively correct the measurement noise covariance of the adaptive Kalman filter, and thus be able to estimate the position and velocity of the object feature point at the current time in the image space more accurately, then the estimation of image Jacobian matrix can be achieved accurately under unknown dynamic environment. The feasibility and superiority of the proposed method can be verified by the simulation and experimental results.

关键词： Jacobian matrices Noise measurement Kalman filters Mathematical model Estimation Current measurement Robots

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Synchronous Detector for GMI Magnetic Sensor Based on Lock-in Amplifier

Synchronous Detector for GMI Magnetic Sensor Based on Lock-i...

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Chinese control Conference (CCC)

作者： Jinchao Wang Fang Jin Lei Zhu Zhi Zhao Hengchang Rao Junlei Song Kaifeng Dong M Wenqin Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

A new concept of a synchronous detector for Giant Magneto-Impedance (GMI) sensors is presented. This concept combines a lock-in amplifier, with outstanding capabilities, high speed and a feedback approach that ensures the amplitude detection with easily adjustable gain. The synchronous detector is capable of measuring high-frequency and very low amplitude signals without the use of diode-based active rectifiers or analog switches. In comparison with most of the commercially available diode-based peak detectors, the linearity of the synchronous detector is generally better, especially for low level amplitudes. The synchronous detector has been used for the amplitude measurement of single frequency sine signal and for the demodulation of amplitude-modulated signal. It has also been successfully integrated in a GMI sensor prototype. Magnetic field measurements in open- and closed-loop of this sensor have been conducted. The measured sensitivity was about 1.02 V/Oe in open-loop while it was 0.12V/Oe in close-loop. The above research provides technical accumulation for the design of sensor nodes based on GMI sensor wireless sensor networks.

关键词： Detectors Magnetic sensors Sensitivity Magnetic cores Voltage measurement Linearity

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Load Frequency control in Power systems via A Sampled-Data controller 37

Load Frequency Control in Power Systems via A Sampled-Data C...

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37th Chinese control Conference, CCC 2018

作者： Shangguau, Xing Chen He, Yong Jiang, Lin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Liverpool Brownlow Hill LiverpoolL69 3GJ United Kingdom

ISBN: (纸本)9789881563941

In modern power systems, load frequency control (LFC) scheme usually operates in the discrete mode, while the most existing LFC schemes are designed in the continuous mode, such that those LFC schemes do not work usually in their best manner in practice. In this paper, a method of state-feedback controller design of load frequency control (LFC) for one-area system is discussed in continuous-discrete mode via sampled-data control scheme. At first, the model of LFC is constructed in continuous-discrete mode by using the input delay method. Then, a new method is present to design a state-feedback controller. Finally, a case study is given to show the effectiveness and the benefits of the proposed method. © 2018 Technical Committee on control Theory, Chinese Association of Automation.

关键词： State feedback

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Load Frequency control in Power systems via A Sampled-Data controller

Load Frequency Control in Power Systems via A Sampled-Data C...

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第37届中国控制会议

作者： XingChen ShangGuan Yong He Lin Jiang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems University of Liverpool

In modern power systems, load frequency control(LFC) scheme usually operates in the discrete mode, while the most existing LFC schemes are designed in the continuous mode, such that those LFC schemes do not work usually in their best manner in practice. In this paper, a method of state-feedback controller design of load frequency control(LFC) for one–area system is discussed in continuous-discrete mode via sampled–data control scheme. At first, the model of LFC is constructed in continuous-discrete mode by using the input delay method. Then, a new method is present to design a state–feedback ***, a case study is given to show the effectiveness and the benefits of the proposed method.

关键词： Power system Load frequency control Sampled-data control State–feedback controller

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Development of electric cart for improving walking ability — application of control theory to assistive technology

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Science China(Information Sciences) 2017年第12期60卷 262-270页

作者： Jinhua SHE Yasuhiro OHYAMA Min WU Hiroshi HASHIMOTO School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Master Program of Innovation for Design & Engineering Advanced Institute of Industrial Technology

This paper explains the development of an electric cart that helps the elderly maintain or improve their physical strength. Unlike commercially available ones, it has a pedal unit that provides some exercise for a user in training his lower limbs. An impedance model describes the feeling of pushing the pedals. The largest pedal load is determined based on a pedaling experiment. An H∞ controller is designed for each of the largest pedal load and virtually no load. A control law, which is based on the concept of dynamic parallel distributed compensation, is designed using the rating of perceived exertion of a driver as a criterion to choose a pedal load between the largest and almost zero. Five university students and twelve elderly people participated experiments to verify the system design and the validity of the system.

关键词： aging Borg’s scale dynamic parallel distributed compensation electrical cart H_∞ control Karvonen formula lower limbs pedaling rating of perceived exertion

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Measurement System of Ferromagnetic Film Magnetic Properties Based on Mazneto-optical Kerr Effect

Measurement System of Ferromagnetic Film Magnetic Properties...

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Chinese control Conference (CCC)

作者： Xueying Fu Wenqin Mo Shun Yuan Liming Xu Junlei Song Kaifeng Dong Fang Jin Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Hubei key Lab. of Adv. Control & Intell. Autom. for Complex Syst. Wuhan China

A new measuring system for magnetic properties of the ferromagnetic thin film has developed based on magneto-optical Kerr effect (MOKE). This system can realize both polar MOKE and longitudinal MOKE measurements through the optimization of optical path and electromagnet's poles. The signal processing software on Lab View has been also designed to acquire the Kerr signal and plot the hysteresis loop. The MOKE measurements have been performed to investigate the magnetic properties of ferromagnetic films such as CoFeSiB, permalloy and NiFe/Ag/NiFe multilayer. The experimental results proved that the system has a high angular accuracy of 0.0008°.

关键词： Magnetic field measurement Magnetic fields Kerr effect Magnetic hysteresis Optical variables measurement Optical films Biomedical measurement

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Multi-Convolution Neural Networks-Based Deep Learning Model for Emotion Understanding

Multi-Convolution Neural Networks-Based Deep Learning Model ...

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Chinese control Conference

作者： Luefeng Chen Min Wu Wanjuan Su Kaoru Hirota Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Tokyo Institute of Technology Yokohama Japan

Multi-convolution neural networks-based deep learning model in combination with multimodal data for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using multi-convolution neural networks, where multilayer convolutions are connected in series and multiple networks are executed in parallel. Moreover, when optimizing the weights of deep neural network by traditional method, it is easy to fall into poor local optimal. To address this problem, a hybrid genetic algorithm with stochastic gradient descent is developed, which has the capacity of inherent implicit parallelism and better global optimization of genetic algorithm so that it can adaptively find the better weights of the network. And in order to speed up the convergence of the proposal, the weights optimized by stochastic gradient descent will be taken as a chromosome of genetic algorithms initial population, and it also can be used as a priori knowledge. To verify the effectiveness of the proposal, experiments on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-the-art methods. Meanwhile, the preliminary application experiments are also carried out and the results indicate that the proposal can be extended to human-robot interaction.

关键词： Feature extraction Genetic algorithms Biological cells Machine learning Sociology Statistics Neural networks

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