Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822465
O. Milbredt
Exponential growth of the number of rules of a multi-dimensional Fuzzy Inference System with growing number of input parameters makes it impractical for humans to populate the description of such a system via the Fuzzy Control Language by hand. In this paper we present a methodology for automatically generating rules. The generation process is influenced by a given weighting of the input parameters. The weighting is derived from a parameter weighting matrix used in the context of Analytic Hierarchy Process. The resulting Fuzzy Inference Systems are intended to be the starting point of an Adaptive Neuro-Fuzzy Inference System. As application of the methodology we present the security management at an airport. Here, Fuzzy Logic is used to evaluate the overall security situation.
{"title":"Parameter weighting for multi-dimensional fuzzy inference systems","authors":"O. Milbredt","doi":"10.1109/ICCAIS.2016.7822465","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822465","url":null,"abstract":"Exponential growth of the number of rules of a multi-dimensional Fuzzy Inference System with growing number of input parameters makes it impractical for humans to populate the description of such a system via the Fuzzy Control Language by hand. In this paper we present a methodology for automatically generating rules. The generation process is influenced by a given weighting of the input parameters. The weighting is derived from a parameter weighting matrix used in the context of Analytic Hierarchy Process. The resulting Fuzzy Inference Systems are intended to be the starting point of an Adaptive Neuro-Fuzzy Inference System. As application of the methodology we present the security management at an airport. Here, Fuzzy Logic is used to evaluate the overall security situation.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115507742","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822459
Shoaib Azam, A. Rafique, M. Jeon
In recent years, category-level object detection has gained a lot of attention. In addition to object localization, estimation of the object pose has practical applications in intelligent transportation, autonomous driving and robotics. Parts based models have been used for pose estimation in recent years, but these models depend on manual supervision or require a complex algorithm to locate the object parts. In this work, we have used Convolutional Neural Network for the pose estimation of vehicle in an image. The advantage of multiple classifications of objects at the same time motivates us to choose the convolutional neural network. We make use of state-of-the-art implementation of convolution neural network named the Region Based Convolutional Neural Network(FASTER-RCNN) for estimating the pose of vehicle. We annotate the comprehensive cars dataset of Stanford, required for training the model and upon testing we have achieved good results with good accuracy.
{"title":"Vehicle pose detection using region based convolutional neural network","authors":"Shoaib Azam, A. Rafique, M. Jeon","doi":"10.1109/ICCAIS.2016.7822459","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822459","url":null,"abstract":"In recent years, category-level object detection has gained a lot of attention. In addition to object localization, estimation of the object pose has practical applications in intelligent transportation, autonomous driving and robotics. Parts based models have been used for pose estimation in recent years, but these models depend on manual supervision or require a complex algorithm to locate the object parts. In this work, we have used Convolutional Neural Network for the pose estimation of vehicle in an image. The advantage of multiple classifications of objects at the same time motivates us to choose the convolutional neural network. We make use of state-of-the-art implementation of convolution neural network named the Region Based Convolutional Neural Network(FASTER-RCNN) for estimating the pose of vehicle. We annotate the comprehensive cars dataset of Stanford, required for training the model and upon testing we have achieved good results with good accuracy.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127504589","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822461
Hae-Rim Shin, Jeonghwan Gwak, Jongmin Yu, M. Jeon
As closed circuit television which had been used only for surveillance or identification has developed rapidly the research on intelligent surveillance systems is getting increased interest. Above all, abnormal event detection is becoming an essential part of surveillance systems by detecting or identifying actions or situations which are not commonly occurred in general. In this work, we propose an abnormal event detection method using trajectory modeling with an automatic scene-adaptive cuboid determination scheme. First, we constructed a human appearance model to determine the human size without using any detection method. Then, HOG feature extracted from human images which is the predetermined input is used to construct a human appearance model. We applied a background subtraction to input datasets and then compared HOG feature extracted from the bounding box of the foreground with the human appearance model. The human size is determined by the size of the foreground bounding box with the highest similarity. With the ratio obtained through the experiments, the cuboid size is calculated according to the human size and histogram of oriented tracklets model is constructed by the cuboid size. We used the UCSD dataset to validate the proposed approach. From the experimental results, we verified the significance of the proposed AED method adopting the automatic scene-adaptive cuboid size determination scheme.
{"title":"Feature flow-based abnormal event detection using a scene-adaptive cuboid determination method","authors":"Hae-Rim Shin, Jeonghwan Gwak, Jongmin Yu, M. Jeon","doi":"10.1109/ICCAIS.2016.7822461","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822461","url":null,"abstract":"As closed circuit television which had been used only for surveillance or identification has developed rapidly the research on intelligent surveillance systems is getting increased interest. Above all, abnormal event detection is becoming an essential part of surveillance systems by detecting or identifying actions or situations which are not commonly occurred in general. In this work, we propose an abnormal event detection method using trajectory modeling with an automatic scene-adaptive cuboid determination scheme. First, we constructed a human appearance model to determine the human size without using any detection method. Then, HOG feature extracted from human images which is the predetermined input is used to construct a human appearance model. We applied a background subtraction to input datasets and then compared HOG feature extracted from the bounding box of the foreground with the human appearance model. The human size is determined by the size of the foreground bounding box with the highest similarity. With the ratio obtained through the experiments, the cuboid size is calculated according to the human size and histogram of oriented tracklets model is constructed by the cuboid size. We used the UCSD dataset to validate the proposed approach. From the experimental results, we verified the significance of the proposed AED method adopting the automatic scene-adaptive cuboid size determination scheme.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128571863","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822441
Nicholas Chong, S. Nordholm, B. Vo, I. Murray
In a “conference room scenario”, the number of speech sources are not known a priori and the number of speech sources which are active remains unknown as these speech sources appear and disappear throughout the measurement period. Furthermore, the speech sources are moving so their mixing parameters change with time. As a result of this, traditional source separation techniques are limited by their capability to properly attribute the correct mixing parameters to the respective sources. The “conference room scenario” problem is very challenging as it involves the localization, tracking and separation of a time varying number of moving speech sources. An online solution which systematically solves “conference room scenario” problem by solving the source localization, tracking and separation in stages is proposed in this paper.
{"title":"Tracking and separation of multiple moving speech sources via cardinality balanced multi-target multi Bernoulli (CBMeMBer) filter and time frequency masking","authors":"Nicholas Chong, S. Nordholm, B. Vo, I. Murray","doi":"10.1109/ICCAIS.2016.7822441","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822441","url":null,"abstract":"In a “conference room scenario”, the number of speech sources are not known a priori and the number of speech sources which are active remains unknown as these speech sources appear and disappear throughout the measurement period. Furthermore, the speech sources are moving so their mixing parameters change with time. As a result of this, traditional source separation techniques are limited by their capability to properly attribute the correct mixing parameters to the respective sources. The “conference room scenario” problem is very challenging as it involves the localization, tracking and separation of a time varying number of moving speech sources. An online solution which systematically solves “conference room scenario” problem by solving the source localization, tracking and separation in stages is proposed in this paper.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127492544","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822445
Stefan Krebs, Lukas Köhrer, S. Hohmann
During the modelling of technical systems, the developer of the model is always faced with uncertain quantities due to non-ideal measurement devices. In contrast to classical stochastical approaches to handle these uncertainties, guaranteed approaches represent an emerging alternative. They allow on the one hand a direct application of the usually given error bounds of measurements and on the other hand a provision of guarantees regarding a model's output. One interesting application area of such methods are safety-critical systems such as electrical traction drives. In this paper, a new methodology to model a voltage source inverter considering unknown but bounded measurement uncertainties during the identification and the operation is presented. The provision of output intervals including the real output voltages is proven by simulations and experiments.
{"title":"A new modelling and identification approach for guaranteed inclusion of a voltage source inverter's output voltages","authors":"Stefan Krebs, Lukas Köhrer, S. Hohmann","doi":"10.1109/ICCAIS.2016.7822445","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822445","url":null,"abstract":"During the modelling of technical systems, the developer of the model is always faced with uncertain quantities due to non-ideal measurement devices. In contrast to classical stochastical approaches to handle these uncertainties, guaranteed approaches represent an emerging alternative. They allow on the one hand a direct application of the usually given error bounds of measurements and on the other hand a provision of guarantees regarding a model's output. One interesting application area of such methods are safety-critical systems such as electrical traction drives. In this paper, a new methodology to model a voltage source inverter considering unknown but bounded measurement uncertainties during the identification and the operation is presented. The provision of output intervals including the real output voltages is proven by simulations and experiments.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115189084","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822449
Xiuwei Xia, Qian Sun, Ya Zhang, Yanyan Wang, Yue Zhang
The ship deformation is an inevitable and severe problem for surface ships, especially when the ship is large or the sea condition is rough. Moreover, the positioning or detecting precision of the shipboard equipment will significantly decreases due to the ship deformation. So it is of great significance that estimating the ship deformation angle and restraining its effect in practice. Since ship deformation measurement technologies are mostly under theory simulation phases at present, we proposed a novel measurement technology based on actual ship test. In this method, the Quasi-static model of the ship deformation angle was presented taken the measuring velocity and the slowly varying feature of the static deforming angle into consideration. Established Markov model and Quasi-static model based on the actual ship experiments, the ship deformation angle can be estimated with the Kalman Filter (KF). And the experiment results showed that the ship deformation angle, including the dynamic deformation angle and the slowly changing deformation angle, can be estimated commendably with the Quasi-static model and angular rate matching. Thus, this proposed method can not only improve the estimated accuracy of the deformation angle in various application environments, verified its effectiveness and superiority, but also prove powerful support for the practical application of the ship deformation measurement.
{"title":"Ship deformation measurement based on angular rate matching method and Quasi-static model","authors":"Xiuwei Xia, Qian Sun, Ya Zhang, Yanyan Wang, Yue Zhang","doi":"10.1109/ICCAIS.2016.7822449","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822449","url":null,"abstract":"The ship deformation is an inevitable and severe problem for surface ships, especially when the ship is large or the sea condition is rough. Moreover, the positioning or detecting precision of the shipboard equipment will significantly decreases due to the ship deformation. So it is of great significance that estimating the ship deformation angle and restraining its effect in practice. Since ship deformation measurement technologies are mostly under theory simulation phases at present, we proposed a novel measurement technology based on actual ship test. In this method, the Quasi-static model of the ship deformation angle was presented taken the measuring velocity and the slowly varying feature of the static deforming angle into consideration. Established Markov model and Quasi-static model based on the actual ship experiments, the ship deformation angle can be estimated with the Kalman Filter (KF). And the experiment results showed that the ship deformation angle, including the dynamic deformation angle and the slowly changing deformation angle, can be estimated commendably with the Quasi-static model and angular rate matching. Thus, this proposed method can not only improve the estimated accuracy of the deformation angle in various application environments, verified its effectiveness and superiority, but also prove powerful support for the practical application of the ship deformation measurement.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117082931","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822467
Qian Zhang, Seung-Hyo Park, T. Song
In this paper, two smoothing filters are proposed to address the 3D angle-only target tracking. One is smoothing extended Kalman filter (sEKF) and the other one is smoothing modified gain extended Kalman filter (sMGEKF). Both of them are based on Rauch-Tung-Striebel (RTS) smoothing. Compared to the traditional approaches (e.g., the EKF and the MGEKF) used in passive localization, the proposed filters have potential advantages in tracking accuracy. Both new filters are applied in 3D angle-only filtering problems and simulation results demonstrate the advantages of these two approaches.
{"title":"Improved 3D angle-only target tracking with smoothing","authors":"Qian Zhang, Seung-Hyo Park, T. Song","doi":"10.1109/ICCAIS.2016.7822467","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822467","url":null,"abstract":"In this paper, two smoothing filters are proposed to address the 3D angle-only target tracking. One is smoothing extended Kalman filter (sEKF) and the other one is smoothing modified gain extended Kalman filter (sMGEKF). Both of them are based on Rauch-Tung-Striebel (RTS) smoothing. Compared to the traditional approaches (e.g., the EKF and the MGEKF) used in passive localization, the proposed filters have potential advantages in tracking accuracy. Both new filters are applied in 3D angle-only filtering problems and simulation results demonstrate the advantages of these two approaches.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127093825","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822425
Seunghun Cha, SeungYong Shin, JunHyuk Choi, D. Yeom
Homodyne Frequency Modulated Continuous Wave (FMCW) radar results LO (Local Oscillator) signal leakage from structural properties of a transceiver. The phenomenon of LO signal leakage degrades high resolution performance. Therefore many researchers have been trying to overcome and improve the technical shortcoming of homodyne transceiver. This paper proposes new signal processing techniques and implementations to improve high angular resolution estimation for homodyne FMCW radar. It examines several multiple signal classification (MUSIC) algorithms such as conventional, Forward/Backward spatial smoothing, and beamspace algorithms and presents typical high resolution signal processing method before describing the proposed signal processing techniques and the results of simulation and real experiment. The high resolution performance of the proposed method is compared to that of general high resolution signal processing based on conventional MUSIC, Forward/Backward spatial smoothing (FBSS) MUSIC, and beamspace (BS) MUSIC algorithms in terms of directions of arrival (DOA).
{"title":"Signal processing techniques for improving angular resolution performance in homodyne FMCW radar","authors":"Seunghun Cha, SeungYong Shin, JunHyuk Choi, D. Yeom","doi":"10.1109/ICCAIS.2016.7822425","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822425","url":null,"abstract":"Homodyne Frequency Modulated Continuous Wave (FMCW) radar results LO (Local Oscillator) signal leakage from structural properties of a transceiver. The phenomenon of LO signal leakage degrades high resolution performance. Therefore many researchers have been trying to overcome and improve the technical shortcoming of homodyne transceiver. This paper proposes new signal processing techniques and implementations to improve high angular resolution estimation for homodyne FMCW radar. It examines several multiple signal classification (MUSIC) algorithms such as conventional, Forward/Backward spatial smoothing, and beamspace algorithms and presents typical high resolution signal processing method before describing the proposed signal processing techniques and the results of simulation and real experiment. The high resolution performance of the proposed method is compared to that of general high resolution signal processing based on conventional MUSIC, Forward/Backward spatial smoothing (FBSS) MUSIC, and beamspace (BS) MUSIC algorithms in terms of directions of arrival (DOA).","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131865803","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822428
Xiaocong Ma, Wei Yang, Heli Gao
In synthetic aperture radar (SAR) images, moving objects appear defocusing. Traditional azimuth velocity estimation methods ignore the displacement error caused by defocusing, which lead to the pixel offset measurement error among sequential images. In order to correct this error, a velocity measurement approach by moving target refocusing is presented in this paper. A novel azimuth multi-angle spaceborne SAR imaging mode is introduced to get sequential images, and effects of azimuth velocity on targets are presented as well. Moreover, azimuth velocity measurement method is derived to get the initial estimation value of the azimuth velocity. By using the initial estimation value, a refocusing approach is given, by compensating the quadratic residual phase and the time-shift phase caused by object moving. Consequently, a more precise azimuth velocity estimation result can be get by implementing the azimuth velocity measurement method again. Finally, the approach is verified by simulation of a point target with azimuth velocity.
{"title":"Velocity measurement by refocusing approach in azimuth multi-angle spaceborne SAR imaging mode","authors":"Xiaocong Ma, Wei Yang, Heli Gao","doi":"10.1109/ICCAIS.2016.7822428","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822428","url":null,"abstract":"In synthetic aperture radar (SAR) images, moving objects appear defocusing. Traditional azimuth velocity estimation methods ignore the displacement error caused by defocusing, which lead to the pixel offset measurement error among sequential images. In order to correct this error, a velocity measurement approach by moving target refocusing is presented in this paper. A novel azimuth multi-angle spaceborne SAR imaging mode is introduced to get sequential images, and effects of azimuth velocity on targets are presented as well. Moreover, azimuth velocity measurement method is derived to get the initial estimation value of the azimuth velocity. By using the initial estimation value, a refocusing approach is given, by compensating the quadratic residual phase and the time-shift phase caused by object moving. Consequently, a more precise azimuth velocity estimation result can be get by implementing the azimuth velocity measurement method again. Finally, the approach is verified by simulation of a point target with azimuth velocity.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132626654","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}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822452
Shidong Ma, Guoqing Yang
Because of the helicopter nonlinear dynamics characteristics, it is very difficult to guarantee system stability by using classical linear system control method, in order to solve this problem, helicopter flight control model is designed and implemented using nonlinear dynamic inversion control methods in this paper. By grouping helicopter state variables, “Partial Inversion” circuits are divided. The control circuit of each group state variable is designed separately; in the dynamic inversion flight control model, inner circuit is included by outer circuit. In inner and outer circuit, nonlinear system transforms to linear system by feedback linearization method, control parameters can be designed based on linear system theory. By inner and outer circuit computing, helicopter tracking the input attitude angle and the input overload, the flight control model is implemented. The Black Hawk helicopter data is used to validate the dynamic inversion control model, the results show that the output response speed of each control channel is fast, and the response signals follows the input signals quickly and precisely. The nonlinear dynamic inversion flight control model simplifies the helicopter flight control circuit design, various helicopter flexible maneuvers are realized, and the control results are satisfied.
{"title":"Helicopter nonlinear dynamic inversion flight control model design","authors":"Shidong Ma, Guoqing Yang","doi":"10.1109/ICCAIS.2016.7822452","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822452","url":null,"abstract":"Because of the helicopter nonlinear dynamics characteristics, it is very difficult to guarantee system stability by using classical linear system control method, in order to solve this problem, helicopter flight control model is designed and implemented using nonlinear dynamic inversion control methods in this paper. By grouping helicopter state variables, “Partial Inversion” circuits are divided. The control circuit of each group state variable is designed separately; in the dynamic inversion flight control model, inner circuit is included by outer circuit. In inner and outer circuit, nonlinear system transforms to linear system by feedback linearization method, control parameters can be designed based on linear system theory. By inner and outer circuit computing, helicopter tracking the input attitude angle and the input overload, the flight control model is implemented. The Black Hawk helicopter data is used to validate the dynamic inversion control model, the results show that the output response speed of each control channel is fast, and the response signals follows the input signals quickly and precisely. The nonlinear dynamic inversion flight control model simplifies the helicopter flight control circuit design, various helicopter flexible maneuvers are realized, and the control results are satisfied.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1721 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129436648","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}
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