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15th International Conference on Space Operations, SpaceOps 2018

作者： He, Lei Liu, Xiaolu Chu, Xiaogeng Chen, Yuning Chen, Yingwu Liu, Ke College of System Engineering National University of Defense Technology Changsha410073 China Delft University of Technology P.O. Box 5031 Delft2600 GA Netherlands College of Mechatronics Engineering and Automation National University of Defense Technology Changsha410073 China

ISBN: (数字)9781624105623

ISBN: (纸本)9781624105623

The traditional ground planning of Earth Observation Satellites cannot deal with the uncertainties such as emergency tasks or other relevant new information that arrives close to real time. The autonomous satellites could perform online decision and online planning on-board in an uncertain and dynamic environment. In order to reduce the influences of the uncertainties from the environment, fulfilling more tasks with a good robustness and improving the efficiency of satellites, we have investigated the characteristics of the problem and proposed a Linear Programming model based on Multi-agent Markov Decision Process. Satellites use the ground-calculated policies to make decentralized individual decisions onboard according to their own states and observations without communications. Periodic communications can be used to improve the total reward. We have designed computational experiments to test the performance of the proposed method on different numbers of agents, replanning horizons and communication gaps. The results show that because of the proposed method, the satellites can autonomously make decisions to observe the targets and can react to the unexpected emergencies in the uncertain environment including the real-time observation tasks and cloud cover information that arrives close to real time. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Satellites

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Big Data Mining Method of Thermal Power Based on Spark and Optimization Guidance

Big Data Mining Method of Thermal Power Based on Spark and O...

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Data Driven Control and Learning Systems (DDCLS)

作者： Mingcheng Song Li Jia Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai P.R. China Shanghai Key Laboratory of Power Station Automation Technology Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai P. R. China

ISBN: (纸本)9781538626191

With the increasing degree of information technology in the electric-power industry, the amount of big data in thermal power has increased geometrically. To address the problem of the computational bottlenecks in traditional data mining deal with big data of thermal power, big data mining of thermal power method based on Spark is presented in this paper. According to the characteristics of the actual operation of the unit, the proposed method determines the steady-state conditions of big data of thermal power and divides the working conditions based on external constraints. In addition, data mining method based on distributed computing is used to mine big data of thermal power to get the strong association rules, thus the best value of the parameters under each working condition can be got. Lastly, the historical knowledge base is established, which can guide the operation of the unit by the proposed method. This method is applied to a 300 MW unit in a power plant in Anhui Province, and mines the operation data of the unit for 10 days in a month. The results of simulation show that the proposed method can effectively mine big data of thermal power and has the advantage of computational efficiency compared with traditional data mining for big data.

关键词： Big Data Data mining Sparks Employee welfare Indexes Optimization Knowledge based systems

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Multi-objective Optimization for Thermal Power Plant Operation Based on Improved Working Condition

Multi-objective Optimization for Thermal Power Plant Operati...

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Data Driven Control and Learning Systems (DDCLS)

作者： Ling-zhi Ye Li Jia Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai P.R. China Shanghai Key Laboratory of Power Station Automation Technology Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai P. R. China

ISBN: (纸本)9781538626191

A multi-objective optimization based on improved K-means algorithm for thermal power plant operation is proposed in this paper. First, an improved K-means algorithm that aims at updating the method of selecting the clustering number and initial clustering center is applied to divide unit load and coal quality condition. Furthermore, a multi-objective optimization method is developed to realize the balance between the economic indicator and the environmental indicator, thus the corresponding optimal operation parameters of the two performance indicators for each condition can be obtained, which can effectively guide the power station operation. Lastly, taking the historical operation data of a 300MW unit as the experimental object, the simulation results show that the proposed multi-objective optimization based on improved K-means algorithm in this paper is effective and reasonable for the power station operation.

关键词： Power generation Employee welfare Clustering algorithms Optimization methods automation Coal

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Extended State Observer for Nonlinear Time-Varying Dynamic Systems

Extended State Observer for Nonlinear Time-Varying Dynamic S...

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第37届中国控制会议

作者： Qiang Chen Ying Tan Zhen Jia Jie Li Denny Oetomo College of Mechatronics Engineering and Automation National University of Defense Technology Melbourne School of Engineering The University of Melbourne

In this paper,a new extended state observer(ESO) is proposed for a second-order general class of nonlinear dynamic *** tuning the parameters appropriately,it is shown that the proposed ESO can achieve the desired estimation performance under mild *** these assumptions are not necessary,it is shown that if one of them is not satisfied,many ESO proposed in literature cannot ***,the implementation issues are *** results demonstrate the power of the proposed algorithm.

关键词： Extended State Observer General Nonlinear Time-Varying Systems Stability Analysis

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Research on multipath mitigation method for boc signal based on ccrw technology 4

Research on multipath mitigation method for boc signal based...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Ai, Peiyue Li, Changgeng Guo, Xiye Liu, Kai School of Physics and Electronics Central South University Middle Xiaoxiang Road Changsha410083 China College of Mechatronics Engineering and Automation National University of Defense Technology No. 109 Deya Road Changsha410073 China

ISBN: (纸本)9781538683392

Binary Offset Carrier (BOC) modulation technology is gradually replacing the traditional BPSK modulation signal as the main modulation method of the new generation satellite navigation signal due to its superiority in multipath suppression performance and code tracking accuracy. However, the tracking and mis-locking problem of BOC signals has become a key point limiting the widespread application of BOC signals. In this paper, we use code reference waveform (CCRW) technology and optimized Bump-jump (BJ) algorithm to analyze the multipath performance of low-order BOC signals under five code reference waveforms. Aiming at the high peak BOC signal with many peaks and high peak-to-peak ratio, we propose a new code reference waveform ensures the high-order BOC signal has good anti-multipath performance and solves the problem of extremely easy mis-locking of its receiver. © 2018 IEEE.

关键词： Modulation

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Human Motion Sequence Recognition Based on Feature Selection and Support Vector Machine

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IOP Conference Series: Materials Science and engineering 2019年第1期646卷

作者： Yunlei Yu Mei Wang Limeng Lin Chen Zhang College of Mechatronics Engineering and Automation Shanghai University Shanghai 200444 China

Aiming at the problem of human motion sequence recognition, algorithm based on feature selection and support vector machine is proposed. Firstly, the feature extraction of human motion sequences is obtained by key frame and human joint angle calculation. Then, based on the Pearson correlation coefficient and CFS evaluation function, the algorithm of relevance feature selection is used to search the optimal feature subset from the original feature set. By reducing the dimension of the feature set, the difficulty of classification recognition is reduced. In the classification process, the support vector machine is used as the classifier to complete the recognition task of the human motion sequence. Through the recognition experiment and the contrast experiment, the effectiveness of the recognition algorithm based on feature selection and support vector machine is proved.

关键词：

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Delay-Dependent Stability Analysis for Polynomial Fuzzy Systems with Time-V arying Delay via Delay-Partitioning Approach

Delay-Dependent Stability Analysis for Polynomial Fuzzy Syst...

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IEEE International Conference of Intelligent Robotic and Control engineering (IRCE)

作者： Jiafeng Yu Qinsheng Li Chunsong Han Marine Engineering College Jiangsu Maritime Institute Nanjing China College of Mechatronics Engineering and Automation Qiqihar University Qiqihar China

ISBN: (纸本)9781538674178

For polynomial fuzzy system with time-varying delay, this paper presents an new SOS-based delay-dependent stability criteria via delay-partitioning approach. The stability analysis for the augmented systems of the polynomial fuzzy systems with time-varying delay employ parameter-dependent Lyapunov-Krasovskii functional. All the conditions in the proposed approach can be represented as sum-of-squares (SOS) problems.

关键词： Fuzzy systems Delays Stability criteria Time-varying systems Symmetric matrices Cybernetics

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A SISO Neuro-fuzzy Wiener Model Identification by Correlation Analysis Method 6

A SISO Neuro-fuzzy Wiener Model Identification by Correlatio...

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2017 IEEE 6th Data Driven Control and Learning Systems Conference (DDCLS’17)

作者： Qi Xiong Li Jia Yong Chen Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai Key Laboratory of Power Station Automation Technology Department of Automation College of Mechatronics Engineering and Automation Shanghai University Petrochina Changqing Oilfield Company Oil Production Plant No.9

ISBN: (纸本)9781509054626

A novel identification algorithm is presented in this paper for neuro-fuzzy based single-input-single-output(SISO)Wiener model with colored noises. The independent identical distribution(iid) Gaussian random signals are adopted to identify the Wiener system, leading to the separation of linear part from nonlinear counterpart in the identification problem. Therefore,correlation analysis method can be used for the identification of the linear part. Moreover, least-squares-based parameter identification algorithm that can avoid the impact of colored noise is proposed to identify the static nonlinear part. Lastly, an example is used to verify the effectiveness of the proposed method.

关键词： SISO Wiener model Neuro-fuzzy system separable signals correlation analysis method

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Design and Algorithm Research of a GNSS/FOG-SINS Integrated Navigation System for Unmanned Vehicles 36

Design and Algorithm Research of a GNSS/FOG-SINS Integrated ...

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第36届中国控制会议

作者： Han Wang Maosong Wang Kun Wen Wenqi Wu College of Mechatronics Engineering and Automation National University of Defense Technology The University of Calgary

ISBN: (纸本)9781538629185

According to the application requirements of autonomous navigation for unmanned vehicles which mainly used for forest exploration and border patrols,this paper designs a cost effective GNSS/SINS integrated system based on the fiber optic gyro（FOG）.After that,the alignment method of SINS and the integrated navigation algorithm are also *** fusing the valid data of GNSS/FOG-SINS with Kalman filter,the error of inertial devices can be corrected and the high-precision inertial navigation results are used to locate by the satellite navigation *** the end of this paper,the simulation and the vehicle field test are done,from which we can see that the tested accuracy can meet the practical precision requirement of the integrated navigation system when the satellite signal is blocked in the complex terrain environment for one minute.

关键词： Unmanned Vehicles GNSS/FOG-SINS Integrated Navigation Kalman Filter

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Performance analysis of IPMSM based on stress calculation of iron core

Performance analysis of IPMSM based on stress calculation of...

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2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017

作者： Cao, Haidong Wang, Shuang Huang, Surong College of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781538628942

The centrifugal force of rotor and motor interference assembly are the two most important sources of core stress in permanent magnet motor, thus the electromagnetic characteristics of permanent magnet motor are changed by core stress, which causes the error between calculation and the actual value of permanent magnet motor performance. In this essay, the stress equations of rotor centrifuge and stator interference assembly are studied, and the simulation method of permanent magnet motor considering the stress and magnetic properties of stator and rotor core is put forward. Taking an IPMSM as a prototype, the performance and parameters of the motor under the influence of considering stress or not are simulated and compared. The experimental results are compared with the simulation results, and the validity and accuracy of the method are verified. © 2017 IEEE.

关键词： Stators

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