Pub Date : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455534
Mei Fang, Liqing Wang, Zhengguang Wu
This paper deals with h -gain controller synthesis of positive Markov jump systems (PMJSs) with asynchronous modes. Thanks to the hidden Markov model, the closed-loop systems are modeled as hidden Markov jump systems (HMJSs). The definitions of positivity, mean stability, and h -gain are introduced for HMJSs. A necessary and sufficient condition is derived to ensure that the HMJSs are positive and mean stable with h -gain γ that can be solvable by linear programming strategy. Two numerical examples are listed to show the effectiveness of our results.
{"title":"Asynchronous Control of Positive Markov Jump Systems: A Necessary and Sufficient Condition","authors":"Mei Fang, Liqing Wang, Zhengguang Wu","doi":"10.1109/DDCLS52934.2021.9455534","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455534","url":null,"abstract":"This paper deals with h -gain controller synthesis of positive Markov jump systems (PMJSs) with asynchronous modes. Thanks to the hidden Markov model, the closed-loop systems are modeled as hidden Markov jump systems (HMJSs). The definitions of positivity, mean stability, and h -gain are introduced for HMJSs. A necessary and sufficient condition is derived to ensure that the HMJSs are positive and mean stable with h -gain γ that can be solvable by linear programming strategy. Two numerical examples are listed to show the effectiveness of our results.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116944975","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}
Precisely and automatically segment the blood vessels in the gastrointestinal wall and analyze their distribution state, which is of great significance to reduce or even avoid serious complications such as iatrogenic colonic perforation. In this paper, we propose the novel gastrointestinal wall vascular segmentation network (GWVSeg-Net) to capture a wider range of semantic features and improve the ability of inter-class recognition and intra-class aggregation by using the global pyramid attention module (GPA). In addition, in order to improve the ability of the model to accurately distinguish between mucosal folds and vessels, a new loss function is proposed to train the model. Experimental results show that the proposed method is superior to the existing advanced segmentation networks in the performance of gastrointestinal wall vascular segmentation.
{"title":"GWVSeg-Net: An Efficient Method for Gastrointestinal Wall Vascular Segmentation","authors":"Xueting Kong, Cheng Lu, Peng Si, Sheng Li, Jinhui Zhu, Xiongxiong He, Xianhua Ou","doi":"10.1109/DDCLS52934.2021.9455524","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455524","url":null,"abstract":"Precisely and automatically segment the blood vessels in the gastrointestinal wall and analyze their distribution state, which is of great significance to reduce or even avoid serious complications such as iatrogenic colonic perforation. In this paper, we propose the novel gastrointestinal wall vascular segmentation network (GWVSeg-Net) to capture a wider range of semantic features and improve the ability of inter-class recognition and intra-class aggregation by using the global pyramid attention module (GPA). In addition, in order to improve the ability of the model to accurately distinguish between mucosal folds and vessels, a new loss function is proposed to train the model. Experimental results show that the proposed method is superior to the existing advanced segmentation networks in the performance of gastrointestinal wall vascular segmentation.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117168804","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455538
Chuang Yang, Zhe Gao, Xiaoou Ma, Yue Miao
To realize the state estimation of linear continuous-time fractional-order systems, the fractional-order Kalman filter (FOKF) is designed to solve problem on the initial value influence. By using the model transformation, an equivalent equation is obtained such that the state estimation of the transformed model is independent of the initial value. The dimension of the equivalent equation is the same as that of the original system, and the proposed FOKF algorithm based on equivalent equation can effectively reduce the initial value influence on the state estimation. Finally, the effectiveness of the solutions for initial value problem for FOKF is validated by the given simulation example.
{"title":"On initial value problem for fractional-order Kalman filters of linear continuous-time fractional-order systems","authors":"Chuang Yang, Zhe Gao, Xiaoou Ma, Yue Miao","doi":"10.1109/DDCLS52934.2021.9455538","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455538","url":null,"abstract":"To realize the state estimation of linear continuous-time fractional-order systems, the fractional-order Kalman filter (FOKF) is designed to solve problem on the initial value influence. By using the model transformation, an equivalent equation is obtained such that the state estimation of the transformed model is independent of the initial value. The dimension of the equivalent equation is the same as that of the original system, and the proposed FOKF algorithm based on equivalent equation can effectively reduce the initial value influence on the state estimation. Finally, the effectiveness of the solutions for initial value problem for FOKF is validated by the given simulation example.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116420935","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455684
Tingli Su, Jian Li, Ai-Qiang Yang, Xue-bo Jin, Jianlei Kong, Yu-ting Bai
The identification of the health status of buildings has been paid more and more attention by all sectors of the society. The early warning of catastrophes or the assessment of the damage degree and residual life of building structures after catastrophes has become a hot topic for scholars from all over the world. In order to improve the performance of building health state recognition, a novel framework based on multi-channel convolution neural network fusion is proposed in this paper. By combining the output results of different convolution neural networks, temporal information and spatial information are used to achieve the accurate classification of building health status. Eventually, with the data collected by the sensor during the earthquake, the proposed framework is proved to be effective and superior.
{"title":"Building Health State Recognition Method Based on Multi-channel Convolution Neural Network Fusion","authors":"Tingli Su, Jian Li, Ai-Qiang Yang, Xue-bo Jin, Jianlei Kong, Yu-ting Bai","doi":"10.1109/DDCLS52934.2021.9455684","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455684","url":null,"abstract":"The identification of the health status of buildings has been paid more and more attention by all sectors of the society. The early warning of catastrophes or the assessment of the damage degree and residual life of building structures after catastrophes has become a hot topic for scholars from all over the world. In order to improve the performance of building health state recognition, a novel framework based on multi-channel convolution neural network fusion is proposed in this paper. By combining the output results of different convolution neural networks, temporal information and spatial information are used to achieve the accurate classification of building health status. Eventually, with the data collected by the sensor during the earthquake, the proposed framework is proved to be effective and superior.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122016202","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455477
Tao Xie, Tianzhen Wang
The traditional detection methods of motor winding asymmetry often analyze the zero-sequence component. However, due to the different types of motors, the collection methods are also different. The marine current turbine (MCT) has a complicated sealing method due to the harsh marine environment, and its working conditions are frequently changed by the influence of the marine current flow rate, which makes it challenging to extract the fault characteristics. This paper proposes a novel method, called ECT-PCA, to detect MCT generator winding asymmetry, which includes: acquiring the stator three-phase current and using the extended Concordia transform (ECT) to obtain the modulus signal; dividing the modulus signal into an equal-length sample, and performing Fourier transform to obtain the frequency domain amplitude; Then establishing a PCA fault detection model, finally uses T2 and SPE statistics to detect whether the winding asymmetry or not. An experimental platform based on the MCT prototype was built to verify the effectiveness of the proposed method.
{"title":"An ECT-PCA-based Fault Detection Method for Winding Asymmetry of Marine Current Turbine Generator","authors":"Tao Xie, Tianzhen Wang","doi":"10.1109/DDCLS52934.2021.9455477","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455477","url":null,"abstract":"The traditional detection methods of motor winding asymmetry often analyze the zero-sequence component. However, due to the different types of motors, the collection methods are also different. The marine current turbine (MCT) has a complicated sealing method due to the harsh marine environment, and its working conditions are frequently changed by the influence of the marine current flow rate, which makes it challenging to extract the fault characteristics. This paper proposes a novel method, called ECT-PCA, to detect MCT generator winding asymmetry, which includes: acquiring the stator three-phase current and using the extended Concordia transform (ECT) to obtain the modulus signal; dividing the modulus signal into an equal-length sample, and performing Fourier transform to obtain the frequency domain amplitude; Then establishing a PCA fault detection model, finally uses T2 and SPE statistics to detect whether the winding asymmetry or not. An experimental platform based on the MCT prototype was built to verify the effectiveness of the proposed method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116851246","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455450
Jianwei Fan, Jun Huang, Yueyuan Zhang, Haochi Che
This paper deals with functional interval observer design for discrete-time switched systems under stealthy deception attacks. First, the boundaries of the attack are obtained by designing interval observers. Then a two-step method to design the functional observers by zonotope is presented. For the first step, an $H$∞ functional observer is presented and as the second step, the zonotope method is applied to obtain the boundaries of states. An illustrative example provided in the last section demonstrates the effectiveness of the proposed method.
{"title":"Functional interval observer for discrete-time switched system under stealthy attacks","authors":"Jianwei Fan, Jun Huang, Yueyuan Zhang, Haochi Che","doi":"10.1109/DDCLS52934.2021.9455450","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455450","url":null,"abstract":"This paper deals with functional interval observer design for discrete-time switched systems under stealthy deception attacks. First, the boundaries of the attack are obtained by designing interval observers. Then a two-step method to design the functional observers by zonotope is presented. For the first step, an $H$∞ functional observer is presented and as the second step, the zonotope method is applied to obtain the boundaries of states. An illustrative example provided in the last section demonstrates the effectiveness of the proposed method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123936068","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455462
Zhen Xie, G. Hou, Jian-hang Zhang, Congzhi Huang
Built-in test (BIT) technology is widely employed in heavy-duty gas turbine control systems for fault recognition. However, it is difficult to obtain an excellent fault diagnostic ability by using the conventional BIT technology, and the false alarm rate is high. In this paper, a design of intelligent BIT based on improved biologically inspired neural network (BINN) is proposed to reduce false alarm. Firstly, massive historical measurement data of controller module is collected and used as training dataset and test dataset. Secondly, intelligent BIT based on improved BINN is designed to deal with the issue of module state identification and reduce false alarm rate. Finally, the effectiveness of proposed approach is validated by the given extensive numerical simulation results and experimental results.
{"title":"Intelligent Built-in Test Design of Controller Module By Improved Biologically Inspired Neural Network","authors":"Zhen Xie, G. Hou, Jian-hang Zhang, Congzhi Huang","doi":"10.1109/DDCLS52934.2021.9455462","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455462","url":null,"abstract":"Built-in test (BIT) technology is widely employed in heavy-duty gas turbine control systems for fault recognition. However, it is difficult to obtain an excellent fault diagnostic ability by using the conventional BIT technology, and the false alarm rate is high. In this paper, a design of intelligent BIT based on improved biologically inspired neural network (BINN) is proposed to reduce false alarm. Firstly, massive historical measurement data of controller module is collected and used as training dataset and test dataset. Secondly, intelligent BIT based on improved BINN is designed to deal with the issue of module state identification and reduce false alarm rate. Finally, the effectiveness of proposed approach is validated by the given extensive numerical simulation results and experimental results.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124485001","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}
In this paper, an adaptive event-triggered fuzzy tracking control problem is studied for direct current (DC) motor servo systems. Fuzzy logic system (FLS) is introduced to deal with the problem of unknown nonlinear functions. Then, an adaptive event-triggered tracking control scheme is proposed by using backstepping design and event-triggered strategy. The proposed event-triggered tracking controller guarantees that the tracking error converges to an arbitrarily small neighborhood of zero and all the signals in the closed-loop system remain bounded. Finally, the effectiveness of the proposed control scheme is proved by a numerical example.
{"title":"Adaptive Event-triggered Fuzzy Control for DC Motor Servo Systems","authors":"Baomin Li, Xuelian Wang, Linqi Wang, Wenjing Yang, Jianwei Xia","doi":"10.1109/DDCLS52934.2021.9455634","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455634","url":null,"abstract":"In this paper, an adaptive event-triggered fuzzy tracking control problem is studied for direct current (DC) motor servo systems. Fuzzy logic system (FLS) is introduced to deal with the problem of unknown nonlinear functions. Then, an adaptive event-triggered tracking control scheme is proposed by using backstepping design and event-triggered strategy. The proposed event-triggered tracking controller guarantees that the tracking error converges to an arbitrarily small neighborhood of zero and all the signals in the closed-loop system remain bounded. Finally, the effectiveness of the proposed control scheme is proved by a numerical example.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126132128","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455546
Pei-Ming Liu, Zhizong Huang, Xianggui Guo
In this paper, an event-triggered group consensus pinning control strategy is proposed for the second-order nonlinear multi-agent systems (MASs) with directed communication graph under periodic denial-of-service (DoS) attacks, which does not require the MASs to satisfy the in-degree balance condition. On this basis, the state error systems under periodic DoS attacks are established. In addition, it should be pointed out that the control strategy includes the selection method of pinning nodes under the group consensus framework. Furthermore, the sampled-data-based event-triggered mechanism (ETM) reduces the excessive consumption of system resources. Finally, simulation examples are given to verify the effectiveness of the control strategy under periodic DoS attacks with different duration.
{"title":"Event-triggered Secure Group Consensus of Second-order Multi-agent Systems under Periodic DoS Attacks","authors":"Pei-Ming Liu, Zhizong Huang, Xianggui Guo","doi":"10.1109/DDCLS52934.2021.9455546","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455546","url":null,"abstract":"In this paper, an event-triggered group consensus pinning control strategy is proposed for the second-order nonlinear multi-agent systems (MASs) with directed communication graph under periodic denial-of-service (DoS) attacks, which does not require the MASs to satisfy the in-degree balance condition. On this basis, the state error systems under periodic DoS attacks are established. In addition, it should be pointed out that the control strategy includes the selection method of pinning nodes under the group consensus framework. Furthermore, the sampled-data-based event-triggered mechanism (ETM) reduces the excessive consumption of system resources. Finally, simulation examples are given to verify the effectiveness of the control strategy under periodic DoS attacks with different duration.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129695865","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}
For a cyber physical system under multiple cyber attacks, including non-periodic denial-of-service (DoS) attack and stochastic deception attack, we design a dynamic output feedback controller with dynamic event-triggered strategy. We adopts a control strategy based on dynamic trigger conditions, which reduces the number of triggers and saves network resources. Besides, we establish a switched system model to describe the presence of multiple cyber attacks with dynamic event-triggered scheme. Then, according to asymptotic stability theory, dynamic output feedback controller ensuring the switching system stable is designed by using a piecewise Lyapunov-Krasovskii function. Furthermore, the parameters of dynamc event-triggered and controller are derived in a unified framework and sufficient conditions for asymptotic stability can be obtained.
{"title":"Dynamic Event-triggered Scheme and Output Feedback Control for CPS under Multiple Cyber Attacks","authors":"Zhigang Zhang, Jinhai Liu, Shuo Zhang, Hongfei Zhu, Baojin Zhang","doi":"10.1109/DDCLS52934.2021.9455613","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455613","url":null,"abstract":"For a cyber physical system under multiple cyber attacks, including non-periodic denial-of-service (DoS) attack and stochastic deception attack, we design a dynamic output feedback controller with dynamic event-triggered strategy. We adopts a control strategy based on dynamic trigger conditions, which reduces the number of triggers and saves network resources. Besides, we establish a switched system model to describe the presence of multiple cyber attacks with dynamic event-triggered scheme. Then, according to asymptotic stability theory, dynamic output feedback controller ensuring the switching system stable is designed by using a piecewise Lyapunov-Krasovskii function. Furthermore, the parameters of dynamc event-triggered and controller are derived in a unified framework and sufficient conditions for asymptotic stability can be obtained.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131667835","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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