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2018 Chinese Automation Congress, CAC 2018

作者： Li, Xin Xie, Guo Liu, Han Wang, Wenqing Information Processing Xi 'An University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Xi'an China

ISBN: (纸本)9781728113128

Modern industrial equipment plays a vital role in the operation of large industrial systems. Accurate prediction of its remaining useful life will greatly reduce the possibility of unsafe accidents. The internal structure of modern industrial equipment is very complex, and a variety of state monitoring data affect the remaining useful life of the equipment, and the mutual influence between different monitoring data has greatly increased the difficulty of remaining useful life prediction. In this paper, the long short-term memory network in deep learning is used to solve this problem. The long short-term memory network has many advantages in time series prediction. The remaining useful life prediction model of industrial equipment based on long short-term memory network and multivariable monitoring data is established, and aiming at the characteristics of multivariable monitoring data, Mini-batch Gradient Descent algorithm (MBGD) is adopted to train the network. Finally, the engine monitoring data set provided by the NASA prediction center is used to verify the algorithm. The data set is divided into training set and test set, the training set is put into the long short-term memory network to get the prediction model, and then the remaining useful life prediction is carried out by the test set. The prediction accuracy and generalization ability of the algorithm are verified by predicting the remaining useful life of three different turbofan engines. © 2018 IEEE.

关键词： Long short-term memory

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Data Based Fault Diagnosis of Hot Axle for High-Speed Train

Data Based Fault Diagnosis of Hot Axle for High-Speed Train

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2018 Chinese Automation Congress, CAC 2018

作者： Sun, Lanlan Hei, Xinhong Xie, Guo Qian, Fueai Wang, Zhuxin Liu, Ran System Control and Intelligent Information Processing University of Technology Xi'An Shaanxi Key Laboratory of Complex Xi'an China

ISBN: (纸本)9781728113128

The axle temperature is an important performance index for high-speed train axle, and many types of high-precision detection device have been developed. However, because the existing hotbox detection system works by comparing the measured value with fixed and experiential temperature thresholds, without considering the dynamic influence of running environment, the rates of fault and failure alarm are still high. Regarding this problem, this paper is to realize high precision fault diagnosis. Firstly, the characteristics of the temperature rising rates of all axles, the axles on the same side of a carriage, the axles on the same side of a whole train are analyzed. Secondly, the support vector machine (SVM) is employed to establish a data-based fault diagnosis model, and the model is optimized using genetic algorithm. Finally, the proposed method is applied to an actual running data, the analysis results demonstrated the effectiveness and feasibility. © 2018 IEEE.

关键词： Genetic algorithms

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Artillery position control through auto disturbance rejection controller based on fuzzy control

Artillery position control through auto disturbance rejectio...

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2013 5th International Conference on intelligent Human-Machine systems and Cybernetics, IHMSC 2013

作者： Peng, Ning Bai, Yongqiang Luo, Hao Bai, Junlong Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology School of Automation Beijing China

ISBN: (纸本)9780769550114

Considering the characteristics of manipulation and collimation control in traction artillery control system, complex mathematic model, uncertainty and nonlinearity, ADRC (Active Disturbance Rejection controller) with Fuzzy control strategy as position controller was adopted and solved the difficult to adjust the parameters and weak anti-interference in practical engineering application. Through tests, it was shown that the controller was robust and met with the requirement of campaign system to quickly move the target to the given position with high reliability and high precision. © 2013 IEEE.

关键词： controllers

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TIEA: A tradeoff-based interactive multiobjective evolutionary algorithm 7

TIEA: A tradeoff-based interactive multiobjective evolutiona...

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7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016

作者： Chen, Lu Xin, Bin Chen, Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9784990534349

This paper proposes a tradeoff based interactive multiobjective evolutionary algorithm (TIEA). It can support the decision maker (DM) to guide the search towards the DM's most preferred solution by combing evolutionary algorithms with the framework of gradient projection. At each iteration, an evolutionary algorithm is used to generate an approximate Pareto optimal solution. Then, the DM is asked to provide preferences in terms of indifference tradeoffs, the projection of which onto the tangent hyperplane of the Pareto front provides a tradeoff direction. To calculate the projection, an approach to approximate the normal vector of the tangent hyperplane of the Pareto front is developed. Results on nine numerical examples by using TIEA show that TIEA is able to solve multiobjective optimization problems with more than three objectives. Moreover, it can find the Pareto optimal solution that the DM prefers most. © 2016, Fuji technology Press. All rights reserved.

关键词： Evolutionary algorithms

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Vibration-Based Fault Diagnosis for Railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

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Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation *** fault diagnosis for railway point machines becomes a hot *** the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature ***,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection ***,support vector machine is utilized for fault *** comparisons show that the proposed method performs *** diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% ***,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Railway point machine Vibration signal Variational mode decomposition Two-stage feature selection

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Statistical learning makes the hybridization of particle swarm and differential evolution more efficient-A novel hybrid optimizer

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science in China(Series F) 2009年第7期52卷 1278-1282页

作者： CHEN Jie1,2,XIN Bin1,2,PENG ZhiHong1,2 & PAN Feng1,2 1 School of Automatic control,Beijing Institute of technology,Beijing 100081,China 2 Key Laboratory of complex system intelligent control and Decision,Ministry of Education,Beijing 100081,China 1. School of Automatic Control Beijing Institute of Technology Beijing 100081 China 2. Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics differential evolution （DE） and particle swarm optimization （PSO）. In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality.

关键词： global optimization statistical learning differential evolution particle swarm optimization hybridization multimodal functions

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A zeroth-order algorithm for distributed optimization with stochastic stripe observations

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science China(Information sciences) 2023年第9期66卷 297-298页

作者： Yinghui WANG Xianlin ZENG Wenxiao ZHAO Yiguang HONG School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Department of Control Science and Engineering Tongji University

Recent years have seen a rising interest in distributed optimization problems because of their widespread applications in power grids, multi-robot control, and regression *** the last few decades, many distributed algorithms have been developed for tackling distributed optimization problems. In these algorithms, agents over the network only have access to their own local functions and exchange information with their neighbors.

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Modelling Transcriptional Regulation with Fractional Order Differential Equation using Gaussian Process 35

Modelling Transcriptional Regulation with Fractional Order D...

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第35届中国控制会议

作者： JI Ruirui ZHANG Xinxin YAN Xiaomei School of Automation and Information Engineering Xi'an University of Technology Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

A reasonable math model is fundamental to describing gene regulatory mechanism.A new method is proposed to model transcriptional regulation with transcription factor from gene expression profiles using fractional order differential *** Process is employed as a tool to model the latent transcription factor activity and particle swarm optimization algorithm is utilized to optimize the fractional order,kinetic parameters in the model and hyperparameters in kernel *** results of the experiment on real gene expression profiles indicate that the fractional order differential equation fits data better,also the proposed approach is feasible to model transcriptional regulation.

关键词： Transcriptional regulation Fractional order differential equation Gaussian Process Particle swarm optimization

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A new soft switching bidirectional buck or boost DC-DC converter

A new soft switching bidirectional buck or boost DC-DC conve...

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11th International Conference on Electrical Machines and systems, ICEMS 2008

作者： Lei, Dong Xueping, Wang Zhen, Liu Xiaozhong, Liao Department of Automatic Control Beijing Institute of Technology China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education China

ISBN: (纸本)9787506292214

This paper presents a new soft switching bidirectional buck or boost DC-DC converter. Compared to the traditional bidirectional DC-DC converter, the new topology can be used as a buck converter or a boost converter in bidirectional cases for Hybrid Electric Vehicles (HEV) and Electrosorb technology (EST) etc. This new converter has the advantages of simple circuit and control strategy, soft-switching implementation without additional devices, high power density, low cost, light weight and high reliability. The operating principle, theoretical analysis, and design guidelines are provided in this paper. The simulation and the experimental verifications are also presented.

关键词： Boost converter

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Relative Position-Based Collaborative Navigation for Cluster UAVs 7th

Relative Position-Based Collaborative Navigation for Cluster...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Aerospace Science and Industry Group Intelligent Technology Research Institute Co. Ltd. Beijing100074 China

ISBN: (纸本)9789819733316

The inertial equipment carried by UAVs without satellite signal assistance will accumulate errors over time, which cannot meet the requirement of obtaining high-precision cluster navigation information for cluster UAVs in long-duration flights. Aiming at this problem, a scheme for cooperative navigation of cluster UAVs based on relative position assistance is proposed. Firstly, the state equations of the cooperative navigation system are established by modeling the errors of inertial devices of low-precision UAVs;secondly, the relative position information of low-precision UAVs and high-precision UAVs as well as other low-precision UAVs transmitted between UAVs through the data chain is taken as the observation equation;finally, the inertial errors of low-precision UAVs are compensated by using the traceless Kalman filtering for the error compensation, which improves the navigation accuracy. After 30 min simulation results show that the cooperative navigation scheme converges the velocity and position errors of the low-precision UAV to 0.5 m/s and 5 m, respectively, which improves the navigation accuracy greatly. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Unmanned aerial vehicles (UAV)

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