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Research on Handwritten Alphabet Recognition System Based on Extreme Learning Machine

Research on Handwritten Alphabet Recognition System Based on...

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第37届中国控制会议

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

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 *** system is implemented by mixed programming with M ATLAB and visual studio,it can reads,normalize,binarize and extract the handwritten letter *** 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 *** 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 *** with BP neural network and other recognition algorithms,its training times have been reduced by hundreds or even thousands of *** the same time,there is no manual intervention in the entire learning and testing process,which improves the automation of handwriting recognition.

关键词： Handwritten Letter Recognition Extreme Learning Machine Feature Extraction Mixed Programming

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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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A Safety Assessment Method Based on Online Sequential Extreme Learning Machine（OS-ELM） in Deep Drilling Process

A Safety Assessment Method Based on Online Sequential Extrem...

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第37届中国控制会议

作者： Yupeng Li Weihua Cao Chao Gan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Accurate and timely assessment of drilling system is key for achieving safety and efficiency in deep drilling. In this paper, an online assessment model is proposed by applying online sequential extreme learning machine（OS-ELM）. The model has been tested through the actual drilling data for drilling system safety assessment and accidents early warning. By analyzing the mechanism characteristics of accidents, well logging parameters are chosen as the input and accident types are chosen as the output. Owing to the OS-ELM is capable of updating network parameters based on new arriving data without retraining historical data, the model can be updated online for specific formation accidents information to make it more adaptable to a particular environment. The numerical test results show that, comparing with other widely used assessment techniques like support vector machines（SVM） and back propagation（BP）, the proposed model has a higher accuracy and shorter recognition time.

关键词： safety assessment extreme learning machine deep drilling online learning

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Quick and Effective Position control for Planar n-link Underactuated Manipulators Based on Optimization Algorithm

Quick and Effective Position Control for Planar n-link Under...

引用

第37届中国控制会议

作者： Pan Zhang Xuzhi Lai Yawu Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper,a simple one-stage control strategy is developed based on optimization algorithm to quickly realize the position control of a planar n-link（n ≥ 3） underactuated manipulator with a passive first *** continuous control of a planar three-link underactuated manipulator with a passive first joint can be realized,and so can the planar n-link（n ≥ 3） ***,one problem that the number of the variables needing to be optimized will increase with the increase of the number of the links will ***,considering the planar three-link manipulator can be controlled to reach to any target position,we employ the differential evolution（DE） algorithm to optimize the angles of only two active links and the design parameters of the corresponding ***,the angles and the corresponding design parameters of other n — 3 active links are kept being *** this way,all link angles can simultaneously converge to their target *** a planar four-link underactuated manipulator with a passive first joint as an example,the simulation results verify the effectiveness and rapidity of the proposed strategy.

关键词： Planar underactuated manipulators First-order nonholonomic system Differential Evolution algorithm Position control One-stage control

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Finite-time H∞ state estimation for discrete time-delayed stochastic switched genetic regulatory networks with uncertain sojourn probabilities

Finite-time H∞ state estimation for discrete time-delayed s...

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第37届中国控制会议

作者： REN Chuanyu WAN Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the problem of finite-time H∞ state estimation for discrete-time stochastic switched genetic regulatory networks（GRNs） with time-varying delays and exogenous disturbances. A new discrete time-delayed stochastic switched GRN model with uncertain sojourn probabilities is devised, which is more general than the switched GRNs model with completely known sojourn probabilities. The sufficient conditions which guarantee the stochastic finite-time boundedness of the estimation error dynamics with a prescribed H∞ disturbance attenuation level are derived. By solving several matrix inequalities,the state estimator parameters can be obtained. A numerical example is given to illustrate the effectiveness of our results.

关键词： Genetic regulatory networks（GRNs） Finite-time H∞ state estimation Uncertain sojourn probabilities

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Piecewise control Strategy for a Planar Four-link Underactuated Manipulator with Friction

Piecewise Control Strategy for a Planar Four-link Underactua...

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第37届中国控制会议

作者： Haoqiang Chen Xuzhi Lai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A piecewise control strategy is proposed to realize the position-posture control of a planar four-link Active-PassiveActive-Active（APAA） underactuated manipulator（UM）. Specially, the particle swarm optimization（PSO） algorithm is used to obtain the target angle of all links based on the constraints of control objects of the system. The overall control process of the system is divided into two stages: Firstly, we design a fuzzy-PI controller for the first link to realize the control target of the passive link, and the error between the current angle and the desired angle of the passive link is converged to zero by adjusting the velocity of the first link. Secondly, the position mode of the servo controller is adopted to control the active links move to their target angles, respectively. Finally, the experimental results of the real system verify the effectiveness of the proposed control strategy.

关键词： underactuated manipulator planar four-link fuzzy-PI control position-posture control

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A Detection System of Tool Parameter Using Machine Vision

A Detection System of Tool Parameter Using Machine Vision

引用

Chinese control Conference

作者： Hantao Wang Hong Wang Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

This paper suggests a novel technique for the tool parameter measurement based on machine vision. Tool images are captured by using a machine vision system and the outer contour image of the cutter is obtained by using the machine vision technology. The HALCON image processing library is used as the development platform to build the tool parameters test system. Several algorithms including image segmentation, edge extraction and fitting ellipse determination is used for image processing. The tool parameters such as external diameter and contour angle of tool edge can be obtained after rebuilding the contour of tool edge. The proposed scheme is shown to be reliable and effective for the automated tool parameter measurement.

关键词： Tools Image edge detection Machine vision Monitoring Corrosion Milling

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A New Result on H∞ State Estimation of Delayed Static Neural Networks via Augmented Lyapunov-Krasovskii Functional

A New Result on H∞ State Estimation of Delayed Static Neura...

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第37届中国控制会议

作者： Zhenman Gao Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper,the problem on guaranteed H∞ performance state estimation for static neural networks with a timevarying delay is investigated and the corresponding criterion is ***,a novel augmented Lyapunov-Krasovskii functional(LKF) is *** the derivative of the LKF is estimated by the relaxed integral ***,the state estimator can be calculated by solving a set of linear matrix ***,an example is used to illustrate the effectiveness of the proposed method.

关键词： Static neural networks H∞ performance state estimation time-varying delay augmented LKF

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Single-Parameter Optimization Method for Extracting Coupling Matrix from Lossy Filters

Single-Parameter Optimization Method for Extracting Coupling...

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第37届中国控制会议

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

This paper presents a novel single-parameter optimization method for extracting coupling matrix from either measured or electromagnetic simulated S-parameters of a narrow band coaxial-resonator filter with losses. Having had the polynomials of the S-parameters of a filter by the Cauchy method with removing phase shift, the rational polynomials can be *** the rational polynomials having been determined, a single-parameter optimization method is proposed to obtain ε and the coupling matrix with an assigned topology, which can be extracted using well established techniques. The measured Sparameters compared with the S-parameters obtained from the coupling matrix, and the attenuation factor K is easily *** loss effects will be removed after obtaining the value of the attenuation factor K. The approach is useful and can be used in computer-aided tuning of microwave filters. Example is presented to illustrate the validity of the proposed method.

关键词： Parameter optimization coupling matrix coupling matrix extraction computer-aided tuning

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Carbon Efficiency Performance Assessment Method for Sintering Process Based on Fuzzy Synthetic Evaluation

Carbon Efficiency Performance Assessment Method for Sinterin...

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第37届中国控制会议

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

Based on the hierarchical control system of sintering process, a carbon efficiency performance assessment method is proposed. Firstly, performance evaluation model of sintering process is designed according to the characteristics hierarchical control structure of sintering process. Then, the performance index of the comprehensive coke ratio（CCR） in the carbon efficiency optimization layer is designed to achieve the carbon efficiency performance assessment. Next, the performance indexes of burning through point（BTP） control system of the optimization control layer and the fuzzy synthetic evaluation method based on information entropy are designed. The proposed carbon efficiency performance assessment method is implemented on the simulation platform of the sintering process in the laboratory, which effectively realized the performance assessment for sintering process plant level control system, and then provides effective information for the staff to maintain the control system.

关键词： Hierarchical control system Performance assessment method Fuzzy synthetic evaluation Comprehensive coke ratio Burning through point

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