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2018 10th International Conference on Modelling, Identification and Control (ICMIC)最新文献

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Entry Trajectory Reconstruction for an Unpowered Reusable Launch Vehicle Under the Change of Landing Field 着陆场变化下无动力可重复使用运载火箭的进入轨迹重建
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529840
Wenbiao Xu, Xuejing Lan
{"title":"Entry Trajectory Reconstruction for an Unpowered Reusable Launch Vehicle Under the Change of Landing Field","authors":"Wenbiao Xu, Xuejing Lan","doi":"10.1109/ICMIC.2018.8529840","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529840","url":null,"abstract":"This paper presents an entry trajectory reconstruction method for an unpowered reusable launch vehicle (RLV), which can replan a feasible trajectory during the entry flight when the landing field is changed in an emergency. Using the quasi-equilibrium condition, the upper- and lower-bounds of the bank angle are obtained. In order to satisfy the path constraints, a weighted combination of the bounds is proposed to determine the magnitude of the bank angle. Then, the sign of the bank angle is determined based on a lateral planning algorithm. Thus, the trajectory reconstruction process can be simplified as a three-parameter search problem for satisfying the terminal constraints. A secant method provides an effective way to solve this root-finding problem. Finally, the performance of the trajectory reconstruction algorithm is assessed with different alternative landing fields.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130076513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Emotion-Aroused Human Behaviors Perception Using RNNPB 基于RNNPB的情绪激发人类行为感知
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529875
Jie Li, Chenguang Yang, Junpei Zhong, Shi‐Lu Dai
{"title":"Emotion-Aroused Human Behaviors Perception Using RNNPB","authors":"Jie Li, Chenguang Yang, Junpei Zhong, Shi‐Lu Dai","doi":"10.1109/ICMIC.2018.8529875","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529875","url":null,"abstract":"This paper proposes a novel framework to recognize emotions using the algorithm of a recurrent neural network with parameter bias (RNNPB). For this purpose, we performed three simulation experiments aim to explore the relationship between the perception and action. Three types of emotion-driven sequences are fed into the network for training. The training of RNNPB utilizes back-propagation through time (BPTT) method and the parametric bias unit (PB unit) updates in a self-organizing way. The results of the experiments show that the merged sequences can distinguish the emotion better compared to the other two kinds of information.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130366320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Compensation Vehicle Distortion Field and Improvement of Magnetic Target Localization 补偿车辆畸变场及改进磁目标定位
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529892
Zhuoshan Geng, Xin Chen, Chong Kang
{"title":"Compensation Vehicle Distortion Field and Improvement of Magnetic Target Localization","authors":"Zhuoshan Geng, Xin Chen, Chong Kang","doi":"10.1109/ICMIC.2018.8529892","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529892","url":null,"abstract":"Generally, a magnetic target includes ferromagnetic material, which can be generated the magnetic anomaly. Based on the magnetic anomaly, we can use a sensor array to locate a magnetic target. Due to sensors located on a vehicle, the distortion field generated by it can affect the value measured by the magnetic sensor. Therefore, the distortion field needs to be compensated. In this paper, the sensor array with four magnetometers and an inertial instrument is presented. We analyze the relationship between the measurements of each magnetometers in the array. Then, we propose a method for compensating the distortion field generated by the vehicle. In addition, we present a method for locating the magnetic target using the sensor array. Based on the magnetic moment, we formulate an optimization problem for estimating the parameters of the target and develop a dedicated PSO algorithm to solve the optimization. from the experiment results, we can know that the calculated positions of the target by the method were near the true values.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132663824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Time-Series Main Trend Analysis by Adaptive Dynamics Model 自适应动力学模型的时间序列主趋势分析
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529910
Xue-bo Jin, Nian-Xiang Yang, Tingli Su, Jianlei Kong
{"title":"Time-Series Main Trend Analysis by Adaptive Dynamics Model","authors":"Xue-bo Jin, Nian-Xiang Yang, Tingli Su, Jianlei Kong","doi":"10.1109/ICMIC.2018.8529910","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529910","url":null,"abstract":"For high-frequency fluctuations of time-series data, it is necessary to extract and analyze the main trend for many applications. This paper focuses on the main trend analysis by Kalman filter, gives the extraction model and the transform model, and discusses the suitable value for the key parameters to guarantee the system convergence. The high order dimensional dynamics of the main trend are analyzed by the estimate results. The simulations show that the developed method is effective for extracting the main trend of the time-series data and able to explain accurately the characteristics of the main trend.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124356342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Automatic Reading System for Analog Instruments Based on Computer Vision and Inspection Robot for Power Plant 基于计算机视觉和电厂巡检机器人的模拟仪表自动读数系统
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529848
Junzhe Wang, Jian Huang, Rong Cheng
{"title":"Automatic Reading System for Analog Instruments Based on Computer Vision and Inspection Robot for Power Plant","authors":"Junzhe Wang, Jian Huang, Rong Cheng","doi":"10.1109/ICMIC.2018.8529848","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529848","url":null,"abstract":"In this paper, an automatic reading system for analog instruments has been designed for monitoring in power plants. In a general automatic reading system, there are many limitations to the reading correctness and system robustness such as the high cost for the reason that there is only one instrument could be monitored by a single system, the strict restrict of the camera angle, and being not suitable for instruments with dense scales and so on. We present some solutions to overcome these limitations. Firstly, we combine a mobile inspection robot with an image capture device and the image processing method to cut the cost of the monitoring of analog instruments in power plants. Then, we use Hough transform and perspective transform to correct the geometric distortion of images caused by camera angle. Eventually, we get the result of dense scaled instruments based on polar transform. Experiments show that our system performs quite well, and the reading error is less than the results which obtained from the general automatic reading system.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124973098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
CNN-Based Mitosis Detection for Assisting Doctors to Diagnosis 基于cnn的有丝分裂检测辅助医生诊断
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529881
Yunru Bai, Jiwei Liu, Jianfei Liu, Zhewei Zhao, R. Mao
{"title":"CNN-Based Mitosis Detection for Assisting Doctors to Diagnosis","authors":"Yunru Bai, Jiwei Liu, Jianfei Liu, Zhewei Zhao, R. Mao","doi":"10.1109/ICMIC.2018.8529881","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529881","url":null,"abstract":"Breast cancer kills more than 500,000 people every year all over the world. The number of mitotic cells is one important indicator to evaluate breast cancer progressing, and mitotic counting is very tedious and easy to make mistake. Therefore, the development of computer-aided detection (CAD) system is important in diagnosis and treatment of breast cancer. In this paper, we propose a CAD system based on a convolutional neural network (CNN) to automatically count mitotic cells. The proposed system consists of three steps. First, a normalization process is exploited to reduce the illumination variance and noise among different individuals as well as highlight the nuclei regions, which can simplify the problem of mitotic counting. Second, an improved convolutional neural network based on LeN et-5 is established to extract features. Last, Softmax can finally determine the location of mitotic cells. Our CAD system was evaluated on the dataset provide by 2012 ICPR mitosis detection challenge, and experimental results revealed that F1 score achieved 0.884.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122604250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Robust Adaptive Position/Force Control of Multiple Mobile Manipulators with Flexible Joints 具有柔性关节的多移动机械臂位置/力鲁棒自适应控制
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529872
Shurong Li, Pandeng Xu, Baigeng Wang
{"title":"Robust Adaptive Position/Force Control of Multiple Mobile Manipulators with Flexible Joints","authors":"Shurong Li, Pandeng Xu, Baigeng Wang","doi":"10.1109/ICMIC.2018.8529872","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529872","url":null,"abstract":"To solve the positon/force control problem of multiple mobile manipulators with flexible joints, a robust adaptive strategy is given. Firstly, the dynamic model of multiple mobile manipulators with flexible joints is established considering the grasped objects. Then by using position/force error terms, a sliding mode adaptive controller is designed by decoupling the position and force. The controller have good robustness. It can guarantee the position error and force error converge to zero. The Lyapunov stability analysis demonstrates the effectiveness of the given strategy. At last, simulation results show the feasibility of the method vividly.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"338 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134478134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Star Identification Method Based on Mixed Characteristics and LVQ Neural Network 基于混合特征和LVQ神经网络的星识别方法
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529903
Sun Hongchi, Mu Rongjun, Du Huajun
{"title":"A Star Identification Method Based on Mixed Characteristics and LVQ Neural Network","authors":"Sun Hongchi, Mu Rongjun, Du Huajun","doi":"10.1109/ICMIC.2018.8529903","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529903","url":null,"abstract":"Star identification method is the basis of celestial navigation. In order to solve the problem that traditional methods can't adapt to high noise condition, a star identification method bases on LVQ neural network is used for star recognition. Compared with several different characteristics vector, the mixed characteristic vector is selected to train the network. The simulation results show that the recognition rate of this star identification method is 100%, and the recognition rate is better than traditional star identification method in high noise condition.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123830921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Research of Nonlinear Adaptive Control Based on BP Neural Network 基于BP神经网络的非线性自适应控制研究
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529873
Xin Liu, Sufang Wang, Weicun Zhang, Qing Li
{"title":"Research of Nonlinear Adaptive Control Based on BP Neural Network","authors":"Xin Liu, Sufang Wang, Weicun Zhang, Qing Li","doi":"10.1109/ICMIC.2018.8529873","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529873","url":null,"abstract":"This paper presents an adaptive control method for a class of nonlinear system based on BP neural network. BP neural network is used to estimate unknown nonlinear characteristic in the plant, then using the BP instead of the real part nonlinear, at last the controller design is given. In order to control the precise, adding the error compensation. The simulation results show the effectiveness.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114690184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Center Difference Set Membership Filter by Zonotopes for Nonlinear System 非线性系统的分区中心差分集隶属度滤波
2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529850
Rong Cheng, Jian Huang
{"title":"Center Difference Set Membership Filter by Zonotopes for Nonlinear System","authors":"Rong Cheng, Jian Huang","doi":"10.1109/ICMIC.2018.8529850","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529850","url":null,"abstract":"The paper proposes an improved approach to state estimation for nonlinear discrete-time systems based on zonotopes. To overcome the inherent defect of Taylors formula, a lower-order multi-dimensional extension of Stirling's interpolation formula is used to realize the linearization of nonlinear models. A nonlinear programming method is used to optimize the guaranteed margin of linearization error to obtain a more compact bound estimation, thereby reducing the conservativeness of the algorithm. Simulation results have shown the effectiveness and improved performance of the proposed algorithm.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116958753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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