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Chinese control Conference

作者： Junlei Song Qi Liu Shengnan Tian Yi Wei Fang Jin Wenqin Mo Kaifeng Dong Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Aiming at the problems of slow recognition, low efficiency and degree of automation in handwritten letter recognition system at present, a handwritten letter recognition system based on extreme learning machine is designed in this paper. The system is implemented by mixed programming with MATLAB and visual studio, it can reads, normalize, binarize and extract the handwritten letter images. The real-time interactive recognition of handwritten letters can be realized on the basis of training the simple pictures by using the identification model of the extreme learning machine algorithm. The experimental results show that the handwriting recognition system based on extreme learning machine designed in this paper can recognize 98.82% of handwritten letters and greatly reduce learning and testing time. Compared with BP neural network and other recognition algorithms, its training times have been reduced by hundreds or even thousands of times. At the same time, there is no manual intervention in the entire learning and testing process, which improves the automation of handwriting recognition.

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Improving Training-based Reflectance Reconstruction via White-balance and Link Function

Improving Training-based Reflectance Reconstruction via Whit...

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Chinese control Conference

作者： Li-Jun Zhang Jun Jiang Hui Jiang Jing-Jing Zhang Xing Jin School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

An improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance by inserting white balance and link function during the training-based method. The novelty in our method is the use of white-balancing to normalize the scene illumination and link function to transform the reflectance, we use a radial basis function network to model the mapping between camera-specific RGB values and specific reflectance spectra. Experimental results indicate that the proposed method significantly outperforms currently existing methods in terms of spectral error and shape especially under the illumination not present in the training process.

关键词： Lighting Image reconstruction Training Cameras Testing Principal component analysis Reflectivity

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A Smoothing-Type Algorithm for Solving Monotone Weighted Complementarity Problems

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Journal of Physics: Conference Series 2020年第1期1642卷

作者： Xiaoqin Jiang Yujin Huang Department of Public Basic Wuhan Technology And Business University Wuhan Hubei 430065 China School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences 388 Lumo Road Wuhan Hubei 430074 China

The weighted complementarity problem is an extension of the standard finite dimensional complementarity problem. It is well known that the smoothing-type algorithm is a powerful tool of solving the standard complementarity problem. In this paper, we propose a smoothing-type algorithm for solving the weighted complementarity problem with a monotone function, which needs only to solve one linear system of equations and performs one line search at each iteration. We show that the proposed method is globally convergent under the assumption that the problem is solvable. The preliminary numerical results indicate that the proposed method is effective and robust for solving the monotone weighted complementarity problem.

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Suppression of Disturbances in Networked control systems with Time-Varying Delay Based on Equivalent-Input-Disturbance Approach

Suppression of Disturbances in Networked Control Systems wit...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Meiliu Li Jinhua She Zhentao Liu Chuanke Zhang Min Wu Yasuhiro Ohyama Xinkai Chen Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan College of Systems Engineering and Sciences Shibaura Institute of Technology Saitama-shi Saitama Japan

A plant is controlled remotely on a network for a networked control system. Disturbances from the network and surroundings may deteriorate the control performance of such a system. To solve this problem, this paper presents a new method of suppressing an exogenous disturbance for those control systems. The control system has a state observer to estimate the state of the plant and an equivalent-input-disturbance (EID) estimator to produce an estimate of the disturbance on the control input channel in a real-time fashion. The system is divided into two subsystems for the analysis of system stability. A stability condition of the control system with a time-varying delay is presented in terms of a linear matrix inequality. Simulations demonstrate the validity of the method. And a comparative study shows the superior of our method to a conventional Smith-EID control method.

关键词： Stability analysis Observers Networked control systems Delay effects Delays Time-varying systems

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An efficient nondominated sorting algorithm 18

An efficient nondominated sorting algorithm

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2018 Genetic and Evolutionary Computation Conference, GECCO 2018

作者： Wang, Junchen Li, Changhe Diao, Yiya Zeng, Sanyou Wang, Hui School of Automation China University of Geosciences 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 Nanchang Institute of Technology Nanchang China

ISBN: (纸本)9781450357647

Nondominated sorting (NS) is commonly needed in multi-objective optimization to distinguish the fitness of solutions. Since it was suggested, several NS algorithms have been proposed to reduce its time complexity. In our study, we found that their performances are closely related to properties of the distribution of a data set, especially the number of fronts. To address this issue, we propose a novel NS algorithm Filter Sort. We also propose a new benchmark data generator for evaluating the performance of a NS algorithm. Experimental results show that our algorithm is superior to several state-of-the-art NS algorithms in most cases. © 2018 Copyright held by the owner/author(s).

关键词： Multiobjective optimization

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Extended dissipativity analysis of delayed memristive neural networks based on a parameter-dependent lyapunov functional

Extended dissipativity analysis of delayed memristive neural...

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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Lu, Chengda Zhang, Xian-Ming Wu, Min Han, Qing-Long He, Yong School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Software and Electrical Engineering Swinburne University of Technology MelbourneVIC3122 Australia

ISBN: (纸本)9781538666173

This paper is concerned with extended dissipativity analysis of memristive neural networks with time-varying delays. Using the characteristic function technique, a tractable model of a memristive neural network is obtained. This model is similar to a neural network with polytopic uncertain synaptic weights, enabling us to construct a parameter-dependent Lyapunov functional. By combining this functional and some integral inequalities, a novel extended dissipativity criterion is obtained in terms of linear-matrix-inequalities, where different Lyapunov matrices are used for each form of the memristive neural network. Through a numerical example, this criterion is shown to be less conservative than the one based on a common Lyapunov functional. © 2018 IEEE.

关键词： Linear matrix inequalities

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Speech Emotion Recognition Based on Linear Discriminant Analysis and Support Vector Machine Decision Tree

Speech Emotion Recognition Based on Linear Discriminant Anal...

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第37届中国控制会议

作者： Jun-Wei Mao Yong He Zhen-Tao Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

For speech emotion recognition,emotional feature set with high dimension may produce redundant features and influence the recognition *** solve this problem and obtain the optimal emotional feature subset of speech,a feature dimension reduction based on linear discriminant analysis is *** to the confusion degree between different basic emotions,an emotion recognition method based on support vector machine decision tree is *** on speaker-dependent speech emotion recognition using Chinese speech database from institute of automation of Chinese academy of sciences is performed and a speech emotion recognition system is presented,where standard feature sets of the INTERSPEECH and classic classifiers are used in comparative experiments *** results show that the proposal achieves 84.39%recognition accuracy on *** proposal,it would be fast and efficient to discriminate emotional states of diverse speakers from speech,and it would make it possible to realize the interaction between speaker and computer/robot in the future.

关键词： Emotion Recognition Speech Linear Discriminant Analysis Support Vector Machine Decision Tree

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Prediction of ROP and MPV Based on Support Vector Regression Method

Prediction of ROP and MPV Based on Support Vector Regression...

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第37届中国控制会议

作者： Yang Zhou Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

During the drilling process, accurate prediction of drilling efficiency and safety plays a key role in timely adjustment of drilling process state. In general, surface parameters rate of penetration（ROP） and mud pit volume（MPV） are often used as important parameters to judge drilling safety and efficiency due to the bad bottom hole environment and unreliable detection devices. However, most drilling systems are underground, the structure is complex and exists many disturbances, so the state of drilling process is difficult to accurately predict. In this paper, an online support vector regression（OSVR） model is proposed to predict the ROP and MPV. First, the parameters of the model are determined by simple drilling process analysis. Then, the fast fourier transform filtering method is used to filter the high frequency disturbances of the data. Finally, the prediction model is established by support vector regression（SVR） method and the model is continuously updated by the model update method. The simulation results of industrial data show that the proposed model has a good prediction effect.

关键词： Rate of Penetration Mud Pit Volume Drilling Process SVR Method

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Multi-Objective Drilling Trajectory Optimization with A Modified complexity Index

Multi-Objective Drilling Trajectory Optimization with A Modi...

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第37届中国控制会议

作者： Wendi Huang Min Wu Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Drilling trajectory optimization is an important part before drilling process. Since decreasing the cost and increasing the safety of drilling process are contrary to each other, drilling trajectory optimization problems should be modeled as multiobjective optimization problems. For this purpose, proposing appropriate optimization index which meet the requirement of drilling process is necessary. Many researches applied drill-string torque as the safety index. However, the actual drilling trajectory may deviate from the design trajectory. Ignoring this fact may cause the torque prediction too optimistic. In this research, the drill-string torque is combined with tortuosity of drilling trajectory to reduce the optimism of the prediction of drillstring torque. A 3D drilling trajectory optimization problem is formulated as a multi-objective optimization problem, and the objective functions are drilling trajectory length and the modified drill-string torque. Non-dominated sorting genetic algorithm II is applied to solve the multi-objective optimization problem, and optimal pareto set are obtained.

关键词： Drilling trajectory multi-objective optimization drill-string torque

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Study on Maximum Power Point Tracking Based on Parabolic Approximation Method for Photovoltaic Power Generation system

Study on Maximum Power Point Tracking Based on Parabolic App...

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第37届中国控制会议

作者： Rengui Li Zhili Tan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Maximum power point tracking controller is essential to obtain the maximum power from a solar array in the photovoltaic systems as the PV power module varies with the temperature and solar irradiation. In the DC/DC circuit, the maximum power point tracking algorithm based on parabolic approximation method is used. On the basis of analyzing the principle of various tracking methods, the key technology of parabola approximation can be found to find the exact maximum power point.

关键词： Parabolic approximation method Maximum power point tracking MPPT Simulation of MATLAB

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