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IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

作者： Xiaoma Liu Yang Han Hongze Qiu Zhiqiang Zheng College of Mechatronics Engineering and Automation National University of Defense Technology Changsha P. R. China

ISBN: (数字)9781538611715

ISBN: (纸本)9781538611722

Rapid and accurate threat evaluation(TE) of incoming targets is the key part in air defense. In order to evaluate the target threat effectively, a threat evaluation index system is constructed. On this basis, an improved kernel principal component analysis method (KPCA) based on hybrid kernel function is proposed to realize dimension reduction of the index data, particle swarm optimization (PSO) is utilized to optimize the parameters. The threat of targets is evaluated and ranked by the technique for order of reference by similarity to ideal solution method (TOPSIS) with the variance contributions of kernel principal components for weighing the processed data. The proposed method can avoid the subjectivity introduced by traditional methods and make dimension reduction of evaluation index data, thus decreasing the complexity of evaluation and improving real-time performance. The numerical experiment shows that the results obtained by this method are reasonable and realistic.

关键词： Kernel Indexes Principal component analysis Neural networks Optimization Feature extraction Complexity theory

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A Relevant Casual Relation Based Timestamp Order Consistency Control Method in DVE systems 3

A Relevant Casual Relation Based Timestamp Order Consistency...

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2017 IEEE 第3届信息技术与机电一体化工程国际学术会议(ITOEC 2017)

作者： Yunxiao Lv Wei Zhang College of Mechatronics Engineering and Automation National University of Defense Technology College of Computer National University of Defense Technology

In DVE systems,maintaining the consistency of event execution time is the core element to provide a unified view for all nodes in the ***,owing to the fluctuation of message transmission de

ISBN: (纸本)9781509053643;9781509053636

In DVE systems,maintaining the consistency of event execution time is the core element to provide a unified view for all nodes in the ***,owing to the fluctuation of message transmission de

关键词： Virtual environments Process control Delays Fluctuations Usability Control systems Clocks

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Parallel optimization method for product configuration and supplier selection based on interval

Parallel optimization method for product configuration and s...

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2017 International Conference on Computer Technology, Electronics and Communication, ICCTEC 2017

作者： Li, Guoxi Zheng, Jian Zhang, Meng College of Mechatronics Engineering and Automation National University of Defense Technology Changsha China

ISBN: (纸本)9781538657843

In order to realize the rapid product design and development under the uncertain environment, an optimization decision theory and method of product configuration and supplier selection based on interval information is proposed. This study proposes to combine the product configuration and supplier selection, considers multiple uncertain factors existing in the process of development, expresses multiple uncertainties with interval numbers, and establishes an integrated optimization model for interval-based product configuration and supplier selection with product cost, delivery period and product performance as the objective function. By redefining the Pareto dominance relation of the objective function value as interval, the NSGA-? algorithm is improved, and then a series of configuration options are obtained by directly solving the interval integration model. Finally, the typical lathe products are used to verify the method. © 2017 IEEE.

关键词： Genetic algorithms

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Auxiliary Model Based Multi-innovation Stochastic Gradient Identification Methods for Hammerstein Output-Error System

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Journal of Donghua University(English Edition) 2017年第1期34卷 53-59页

作者：冯启亮贾立李峰 Shanghai Key Laboratory of Power Station Automation Technology College of Mechatronics Engineering and Automation Shanghai University Shanghai 200072 China

Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was *** special input signals were used to realize the identification and separation of the Hammerstein *** a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable *** auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein *** auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation *** simulation results show the efficiency of the proposed method.

关键词： Hammerstein output-error system special input signals auxiliary model based multi-innovation stochastic gradient algorithm innovation length

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Coordinated Stochastic Scheduling for Improving Wind Power Adsorption in Electric Vehicles-Wind Integrated Power Systems by Multi-objective Optimization Approach

Coordinated Stochastic Scheduling for Improving Wind Power A...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Yuanzheng Li Zhixian Ni Tianyang Zhao Minghui Yu Yun Liu Lei Wu Key Laboratory of Control of Power Transmission and Conversion (SJTU) Ministry of Education Shanghai School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Electrical and Electronic Engineering Nanyang Technological University Singapore College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Stevens Institute of Technology Hoboken New Jersey USA

Electric vehicles (EVs) and renewable energy (RE), such as wind power, have been widely utilized to meet the sustainable development of our society. To this end, researches on operation performance of the EV-wind integrated power system are important. This paper proposes a coordinated stochastic scheduling model based on a multi-objective optimization approach, which aims to improve wind power adsorption while considering energy conservation and emission reduction of thermal generators. Besides, to conduct comprehensive investigation among these multiple objectives, we formulate the coordinated stochastic scheduling model as a multi-objective optimization problem. Then, a multi-objective optimization algorithm based on a parameter adaptive differential evolution is proposed to solve this problem. Simulation results based on a modified Midwestern US power system verify that the proposed scheduling model could reveal the relationship among multiple objectives, and the integration of EVs can improve wind power adsorption and cost effectiveness of the power system.

关键词： Wind power generation Power systems Scheduling Stochastic processes Wind speed Optimal scheduling

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Fault-Tolerant Control Design against Actuator Faults with Application to UAV Formation Flight 36

Fault-Tolerant Control Design against Actuator Faults with A...

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第36届中国控制会议

作者： Xiang Yu Peng Li Youmin Zhang the Department of Mechanical Industrial and Aerospace EngineeringConcordia University the College of Mechatronics Engineering and Automation at National University of Defense Technology

ISBN: (纸本)9781538629185

This paper presents a fault-tolerant control（FTC） strategy against actuator malfunctions,with application to formation flight of multiple unmanned aerial vehicles（UAVs）.Within the leader-follower context,the FTC mainly consists of the outer-loop control and the inner-loop fault *** reference commands for the follower UAV are generated by the inner-loop of the follower *** inner-loop FTC is designed based on sliding mode control（SMC） and model reference adaptive control（MRAC） approaches,such that the adverse effects induced by failed actuators can be counteracted within finite *** the presented FTC scheme,both the finite-time convergence of the adaptive laws and the finite-time stability of the post-fault UAV can be *** effectiveness of the proposed FTC approach is illustrated by simulations of UAVs formation flight.

关键词： Fault-tolerant control（FTC） unmanned aerial vehicles（UAVs） formation flight actuator faults

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A fast hybrid meta-heuristic algorithm for economic/environment unit commitment with renewables and plug-in electric vehicles 9th

A fast hybrid meta-heuristic algorithm for economic/environm...

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9th International Conference on Swarm Intelligence, ICSI 2018

作者： Yang, Zhile Niu, Qun Guo, Yuanjun Ma, Haiping Qu, Boyang Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Mechatronics and Automation Shanghai University Shanghai China College of Mathematics Physics and Information Shaoxing University Shaoxing China School of Electrical and Information Engineering Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9783319938141

To tackle with the urgent scenario of significant green house gas and air pollution emissions, it is pressing for modern power system operators to consider environmental issues in conventional economic based power system scheduling. Likewise, renewable generations and plug-in electric vehicles are both leading contributors in reducing the emission cost, however their integrations into the power grid remain to be a remarkable challenging issue. In this paper, a dual-objective economic/emission unit commitment problem is modelled considering the renewable generations and plug-in electric vehicles. A novel fast hybrid meta-heuristic algorithm is proposed combing a binary teaching-learning based optimization and the self-adaptive differential evolution for solving the proposed mix-integer problem. Numerical studies illustrate the competitive performance of the proposed method, and the economic and environmental cost have both been remarkably reduced. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Greenhouse gases

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Magnetic anomaly detection with empirical mode decomposition trend filtering

Magnetic anomaly detection with empirical mode decomposition...

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作者： Zhou, Han Pan, Zhongming Zhang, Zhuohang College of Mechatronics Engineering and Automation National University of Defense Technology Changsha410073 China

Magnetic Anomaly Detection (MAD) is a passive method for the detection of ferromagnetic objects. Currently, the performance of a MAD system is limited by the magnetic background noise that is nonstationary and shows self-similarity and long-range correlation. In this paper, we propose an empirical mode decomposition (EMD) trend filtering based energy detector for adaptively detecting the magnetic anomaly signal from the background noise. The input data is first detrended adaptively with the energy-ratio trend filtering approach. Then, the magnetic anomaly signal is detected using an energy detector. The proposed detector does not need any a priori knowledge about the target or assumptions regarding the background noise. Experiments also prove that the proposed detector shows a more stable performance than the existing undecimated discrete wavelet transform (UDWT) based energy detector. Copyright © 2017 The Institute of Electronics, Information and Communication Engineers.

关键词： Empirical mode decomposition

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Soft Sensor Modeling Based on Auxiliary Error Probability Density Function Shape Control 36

Soft Sensor Modeling Based on Auxiliary Error Probability De...

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第36届中国控制会议

作者： Huifeng Tian Li Jia Shanghai Key Laboratory of Power Station Automation Technology Department of AutomationCollege of Mechatronics Engineering and AutomationShanghai University College of Electric and Information Engineering Jiangsu University of Science and Technology

ISBN: (纸本)9781538629185

Soft sensor has been widely used for estimating product quality or other important process variables when online analyzers are not available. In order to cope with estimation performance deterioration when process variables abruptly change, a new soft sensor modeling method based on auxiliary error neuro-fuzzy model is proposed. The model mean square error（MSE） is used as an evaluating index in traditional data-driven modeling, while only seeks the minimum error function from the vision of a single sample without considering the spatial state of model error data points. To overcome this shortcoming, the auxiliary error model and probability density function（PDF） are combined to adjust the model parameter by controlling auxiliary error PDF shape to track a given target PDF. Furthermore, soft sensor model parameters are determined by means of gradient descent method. The actual operation process data of coal-fired power plant are selected as the modeling data to justify the effectiveness of the proposed method, experimental results show that the prediction accuracy and generalization ability of combining auxiliary error neuro-fuzzy model（AENFM） and PDF-based soft sensor modeling method are superior to other three data-driven methods using MSE criterion. The results indicate that the proposed method can be applied to soft sensor modeling of complex nonlinear system.

关键词： Neuro-fuzzy Model Auxiliary Error Probability Density Function Extreme Learning Machine Least Square Support Vector Machine

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Assembly data mining platform based on python 5

Assembly data mining platform based on python

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5th International Conference on Information Science and Cloud Computing, ISCC 2017

作者： Zhang, Kai Li, Guoxi Zhang, Meng College of Mechatronics Engineering and Automation National University of Defense Technology Changsha410073 China

There are rich data in the manufacturing information systems, but they are not utilized in an effective way. The establishement of assembly data mining platform is to take advantage of the data to improve assembly process. Assembly factors and assembly data mining templates are the core tables in the assembly database. The methods of dealing with data vacancies and noise points are pre-set in the data mining templates. Python is used as the data mining engine by script customization and algorithm library encapsulation. Firstly, Python algorithm scripts are customized when programing the platform. Then the platform generates the execution script according to the user operation. Finally, the main program of Python executes the generated script and returns the results. Also, Mlpy is applied to make corresponding algorithm processing module. The functions are pre-compiled so that the assembly technicians without knowledge of data mining can utilize the assembly data to predict the assembly performance and analyse the assembly process. © Copyright owned by the author(s).

关键词： Assembly

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