Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8833078
Xutong Li, Yan Zheng, Tingting Sun
The paper introduces and adopts an improved and unscented kalman filtering algorithm to track moving targets. For issues like large calculation amount, unfavorable real-time performance and non-local effects of samples of this algorithm, scale factors are adaptive selected to simplex sampling with minimum skewness. According to simulation results, on one hand, introduction of the algorithm can reduce calculation amount and increase arithmetic speed. On the other hand, it can decrease errors of non-local effects and high order, and enhance the accuracy of target tracking.
{"title":"Application of an Improved and Unscented Kalman Filtering Algorithm in Target Tracking","authors":"Xutong Li, Yan Zheng, Tingting Sun","doi":"10.1109/CCDC.2019.8833078","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833078","url":null,"abstract":"The paper introduces and adopts an improved and unscented kalman filtering algorithm to track moving targets. For issues like large calculation amount, unfavorable real-time performance and non-local effects of samples of this algorithm, scale factors are adaptive selected to simplex sampling with minimum skewness. According to simulation results, on one hand, introduction of the algorithm can reduce calculation amount and increase arithmetic speed. On the other hand, it can decrease errors of non-local effects and high order, and enhance the accuracy of target tracking.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128497330","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8833371
Huanqing Wang, Wen Bai
In this paper, we design an adaptive fault-tolerant control for a class of strict-feedback nonlinear system to address tracking control problem in the finite-time. Fuzzy logic systems are applied to deal with the unknown nonlinear faults, and the traditional adaptive control and backstepping technique are combined to design controller. It is indicated that the presented controller ensures that the tracking error converges to a small area around the origin and all signals within the closed-loop system remain bounded. The simulation results are supplied to prove the availability of the presented controller.
{"title":"Finite-time adaptive fault-tolerant control for strict-feedback nonlinear systems","authors":"Huanqing Wang, Wen Bai","doi":"10.1109/CCDC.2019.8833371","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833371","url":null,"abstract":"In this paper, we design an adaptive fault-tolerant control for a class of strict-feedback nonlinear system to address tracking control problem in the finite-time. Fuzzy logic systems are applied to deal with the unknown nonlinear faults, and the traditional adaptive control and backstepping technique are combined to design controller. It is indicated that the presented controller ensures that the tracking error converges to a small area around the origin and all signals within the closed-loop system remain bounded. The simulation results are supplied to prove the availability of the presented controller.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129048990","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8833455
Fawei Ge, Kun Li, Wensu Xu, Yi'an Wang
It is difficult for the traditional manual inspection method to satisfy the current management requirements. Now, UAV inspection technology has been used by more and more enterprises. In the UAV inspection, path planning is an important work. An improved grey wolf optimization algorithm is proposed for the path planning of UAV in oilfield environment in this paper. Firstly, the model of the oilfield environment is built; secondly, the initial path is produced by the basic grey wolf optimization (GWO) algorithm; and then, the fruit fly optimization (FOA) algorithm is used to continue the local optimization of the optimal solution; finally, the optimal path is generated. Compared with some other methods, the simulation results show that the improved grey wolf optimization algorithm is effective.
{"title":"Path Planning of UAV for Oilfield Inspection Based on Improved Grey Wolf Optimization Algorithm","authors":"Fawei Ge, Kun Li, Wensu Xu, Yi'an Wang","doi":"10.1109/CCDC.2019.8833455","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833455","url":null,"abstract":"It is difficult for the traditional manual inspection method to satisfy the current management requirements. Now, UAV inspection technology has been used by more and more enterprises. In the UAV inspection, path planning is an important work. An improved grey wolf optimization algorithm is proposed for the path planning of UAV in oilfield environment in this paper. Firstly, the model of the oilfield environment is built; secondly, the initial path is produced by the basic grey wolf optimization (GWO) algorithm; and then, the fruit fly optimization (FOA) algorithm is used to continue the local optimization of the optimal solution; finally, the optimal path is generated. Compared with some other methods, the simulation results show that the improved grey wolf optimization algorithm is effective.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121282714","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8832368
Wenxing Li, H. Du, D. Ning, Weihua Li
In this paper, a robust adaptive sliding mode proportional integral control (RASMPIC) method is proposed for an active vehicle seat suspension system, where the driver’s mass is supposed as an unknown parameter with boundaries. A dynamic active seat suspension system is established at first. Then a sliding mode controller (SMC) is designed to achieve the required ride comfort performance based on the driver’s mass estimated by utilizing an adaptive law where a projecting adaptive algorithm is used to prevent the estimated parameters from surpassing their boundaries to enhance the robustness of the seat suspension system. Also, a proportional and integral (PI) control for driver’s acceleration is added into the controller as RASMPIC for the stabilization of the proposed suspension system. In simulations, sinusoidal vibrations are used to test the controllers and the results show the RASMPIC has a better control performance to reduce driver’s acceleration and improve the driving comfort than SMC and RASMC.
{"title":"Robust Adaptive Sliding Mode PI Control for Active Vehicle Seat Suspension Systems","authors":"Wenxing Li, H. Du, D. Ning, Weihua Li","doi":"10.1109/CCDC.2019.8832368","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832368","url":null,"abstract":"In this paper, a robust adaptive sliding mode proportional integral control (RASMPIC) method is proposed for an active vehicle seat suspension system, where the driver’s mass is supposed as an unknown parameter with boundaries. A dynamic active seat suspension system is established at first. Then a sliding mode controller (SMC) is designed to achieve the required ride comfort performance based on the driver’s mass estimated by utilizing an adaptive law where a projecting adaptive algorithm is used to prevent the estimated parameters from surpassing their boundaries to enhance the robustness of the seat suspension system. Also, a proportional and integral (PI) control for driver’s acceleration is added into the controller as RASMPIC for the stabilization of the proposed suspension system. In simulations, sinusoidal vibrations are used to test the controllers and the results show the RASMPIC has a better control performance to reduce driver’s acceleration and improve the driving comfort than SMC and RASMC.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"73 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123526679","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8832464
Zhuoren Tang, Liwei Xu, Guo-dong Yin, Haoji Liu
Disturbances and information delays can significantly affect the stability of the vehicle platoon. This paper proposes a robust control algorithm for heterogeneous vehicle platoon under external disturbances and wireless communication delays. By employing the approach of equivalent communication delay and deeming road slop and aerodynamic drag as the external disturbance, the error model of vehicle platoon including delay and interference is established firstly. Then, based on the Lyapunov-Krasovskii theorem and H∞ control, one robust control method that can relieve the control conservatism is proposed to reduce the effects of delays and disturbances. To guarantee that the proposed controller has the property of string stability, the criterion that conforms to the L2 stability is presented. A comparative simulation with the traditional string stability controller is applied to prove the effectiveness of raised method.
{"title":"L2 String Stability of Heterogeneous Platoon under Disturbances and Information Delays","authors":"Zhuoren Tang, Liwei Xu, Guo-dong Yin, Haoji Liu","doi":"10.1109/CCDC.2019.8832464","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832464","url":null,"abstract":"Disturbances and information delays can significantly affect the stability of the vehicle platoon. This paper proposes a robust control algorithm for heterogeneous vehicle platoon under external disturbances and wireless communication delays. By employing the approach of equivalent communication delay and deeming road slop and aerodynamic drag as the external disturbance, the error model of vehicle platoon including delay and interference is established firstly. Then, based on the Lyapunov-Krasovskii theorem and H∞ control, one robust control method that can relieve the control conservatism is proposed to reduce the effects of delays and disturbances. To guarantee that the proposed controller has the property of string stability, the criterion that conforms to the L2 stability is presented. A comparative simulation with the traditional string stability controller is applied to prove the effectiveness of raised method.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114966146","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8833002
Wang Limei, Li Longxiang, Song Hongmei
A recurrent wavelet fuzzy neural network (RWFNN) control method combined with global sliding mode control (GSMC) is proposed to solve the problem of dual-axis synchronous error of H-type platform system driven by permanent magnet synchronous linear motor. Firstly, global sliding mode controller is designed to eliminate the approaching mode, reduce tracking error and ensure global robustness in the single-axis of H-type platform system. Recurrent wavelet fuzzy neural network compensator is designed for the dual-axis of H-type platform system, to compensate the synchronous error. The simulation results show that the proposed method not only guarantees the global robustness of the system, but also effectively reduces the synchronous error of the system and improves the tracking accuracy.
{"title":"Global Sliding Mode Control Based on Recurrent Wavelet Fuzzy Neural Network Control for H-type Platform","authors":"Wang Limei, Li Longxiang, Song Hongmei","doi":"10.1109/CCDC.2019.8833002","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833002","url":null,"abstract":"A recurrent wavelet fuzzy neural network (RWFNN) control method combined with global sliding mode control (GSMC) is proposed to solve the problem of dual-axis synchronous error of H-type platform system driven by permanent magnet synchronous linear motor. Firstly, global sliding mode controller is designed to eliminate the approaching mode, reduce tracking error and ensure global robustness in the single-axis of H-type platform system. Recurrent wavelet fuzzy neural network compensator is designed for the dual-axis of H-type platform system, to compensate the synchronous error. The simulation results show that the proposed method not only guarantees the global robustness of the system, but also effectively reduces the synchronous error of the system and improves the tracking accuracy.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121083353","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8832959
Fen Zhao, Penghua Li, Yinguo Li, Yuanyuan Li
Aiming to achieving safe and efficient energy utilization for electric vehicles, research into the monitoring of lithium-ion batteries (LIBs) has become increasingly important. However, various estimation strategies are proposed at the cost of the higher design complexity and the poorer model performance, which are hard to be implemented. Complementarily, in this paper, we propose an Deep Neural Networks (DNNs)-based State of Charge (SOC) observer design for LIBs to ensure safe and reliable battery operations, which avoiding overcharging or over-discharging of the battery. More specifically, a Recursive Neural Networks (RNNs)-based feature extraction model is proposed to obtain sufficient feature information. Then, the well-trained feature vector is integrated into Convolutional Neural Networks (CNNs) to predict the LIBs SOC. In other words, the output of the RNNs are used as the input of the CNNs, which this practice can improve the model performance obviously. Furthermore, the extensive real-world experiments demonstrate that Neural Network-based SOC prediction model can provide faster convergence speed and higher precision in contrast to the optimal method to achieve SOC estimation over regular model.
{"title":"The Li-ion Battery State of Charge Prediction of Electric Vehicle Using Deep Neural Network","authors":"Fen Zhao, Penghua Li, Yinguo Li, Yuanyuan Li","doi":"10.1109/CCDC.2019.8832959","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832959","url":null,"abstract":"Aiming to achieving safe and efficient energy utilization for electric vehicles, research into the monitoring of lithium-ion batteries (LIBs) has become increasingly important. However, various estimation strategies are proposed at the cost of the higher design complexity and the poorer model performance, which are hard to be implemented. Complementarily, in this paper, we propose an Deep Neural Networks (DNNs)-based State of Charge (SOC) observer design for LIBs to ensure safe and reliable battery operations, which avoiding overcharging or over-discharging of the battery. More specifically, a Recursive Neural Networks (RNNs)-based feature extraction model is proposed to obtain sufficient feature information. Then, the well-trained feature vector is integrated into Convolutional Neural Networks (CNNs) to predict the LIBs SOC. In other words, the output of the RNNs are used as the input of the CNNs, which this practice can improve the model performance obviously. Furthermore, the extensive real-world experiments demonstrate that Neural Network-based SOC prediction model can provide faster convergence speed and higher precision in contrast to the optimal method to achieve SOC estimation over regular model.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"17 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125730408","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}
To improve the observation accuracy and shorten the transient time simultaneously, in this paper, we propose a new nonlinear extended state observer (ESO) by using a switching strategy. The convergence of the proposed ESO is proved with explicit error estimation. The effectiveness of the proposed switched nonlinear ESO is demonstrated through numerical simulations and comparison with existing ESOs. The numerical results show that the proposed new ESO is more accurate and the transient time is shorter than the previous ESOs with the same tuning parameter.
{"title":"A New Switching Nonlinear Extended State Observer","authors":"Zhi-liang Zhao, Yi-Yi Wang, Hao-Nan Shi, Zhong-Ping Jiang","doi":"10.1109/CCDC.2019.8832602","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832602","url":null,"abstract":"To improve the observation accuracy and shorten the transient time simultaneously, in this paper, we propose a new nonlinear extended state observer (ESO) by using a switching strategy. The convergence of the proposed ESO is proved with explicit error estimation. The effectiveness of the proposed switched nonlinear ESO is demonstrated through numerical simulations and comparison with existing ESOs. The numerical results show that the proposed new ESO is more accurate and the transient time is shorter than the previous ESOs with the same tuning parameter.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114890919","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 : 2019-06-03DOI: 10.1109/CCDC.2019.8832927
S. Yong, Li Xinqi, Wang Yang
With the rapid development of shared bicycles, large-scale bicycles have flooded into the streets, traditional parking racks have been unable to meet the demand, and stereo garages have become more and more widely used. The intelligent of the three-dimensional garage puts forward higher requirements on the computing power and logic processing capability of the microprocessor of its control system. By analyzing the characteristics and structural characteristics of the lifting and traversing mechanism, this paper designs a stereo bicycle library system based on STM32. Through the STM32 main control chip and RFID high-frequency reader module and corresponding hardware structure, the bicycle garage smart card access function is realized; Through the touch screen and the voice module, the user is prompted to use the password or swipe to access the vehicle, and the garage storage vehicle is displayed in real time, so that the user can conveniently and quickly access the vehicle through various ways under the voice prompt. The system can stably and efficiently control the normal operation of the stereo garage, and has the characteristics of space saving, low cost and convenient operation.
{"title":"Design of Stereo Bicycle Library System Based on STM32","authors":"S. Yong, Li Xinqi, Wang Yang","doi":"10.1109/CCDC.2019.8832927","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832927","url":null,"abstract":"With the rapid development of shared bicycles, large-scale bicycles have flooded into the streets, traditional parking racks have been unable to meet the demand, and stereo garages have become more and more widely used. The intelligent of the three-dimensional garage puts forward higher requirements on the computing power and logic processing capability of the microprocessor of its control system. By analyzing the characteristics and structural characteristics of the lifting and traversing mechanism, this paper designs a stereo bicycle library system based on STM32. Through the STM32 main control chip and RFID high-frequency reader module and corresponding hardware structure, the bicycle garage smart card access function is realized; Through the touch screen and the voice module, the user is prompted to use the password or swipe to access the vehicle, and the garage storage vehicle is displayed in real time, so that the user can conveniently and quickly access the vehicle through various ways under the voice prompt. The system can stably and efficiently control the normal operation of the stereo garage, and has the characteristics of space saving, low cost and convenient operation.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132436750","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}
Feature point matching is an essential section in image matching. Traditional feature point matching algorithm uses merely the information of feature points such as the descriptors, and on some occasions this may lead to a loss of feature points or even mismatches. This paper proposed an improved feature point matching algorithm based on rectangle template matching. Provided with 2-dimensional coordinates of feature points, a novel parameter named "inner-point index" is calculated and used to extract templates from the input image. On the basis of template matching between the input image and the other image, the process of feature point matching is carried out between templates and the matched areas, using Brute Force matching algorithm. Experimental results show that the proposed algorithm can obtain more correct feature point matches, thus enhances the accuracy of feature point matching.
{"title":"Improved Rectangle Template Matching Based Feature Point Matching Algorithm","authors":"Zhiyuan Liu, Yanning Guo, Zhen Feng, Shaojiang Zhang","doi":"10.1109/CCDC.2019.8833208","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833208","url":null,"abstract":"Feature point matching is an essential section in image matching. Traditional feature point matching algorithm uses merely the information of feature points such as the descriptors, and on some occasions this may lead to a loss of feature points or even mismatches. This paper proposed an improved feature point matching algorithm based on rectangle template matching. Provided with 2-dimensional coordinates of feature points, a novel parameter named \"inner-point index\" is calculated and used to extract templates from the input image. On the basis of template matching between the input image and the other image, the process of feature point matching is carried out between templates and the matched areas, using Brute Force matching algorithm. Experimental results show that the proposed algorithm can obtain more correct feature point matches, thus enhances the accuracy of feature point matching.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128397945","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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