Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8832524
Xue Feng, Long Wang, S. Levin
Disease-behavior systems focus on the feedback loop between disease prevalence and individual vaccinating behavior: prevalent diseases stimulate individuals to vaccinate to avoid infection, high vaccination coverage mitigates the spread of diseases, then payoff-maximizers prefer not to vaccinate, which leads to the increase of non-vaccinators and facilitates disease outbreaks. In such coupled systems, individual vaccinating behavior usually depends on the perceived rather than real payoffs of infection and vaccination, which has not been fully explored. In this paper, we study the dynamics of disease-behavior systems and associated economic costs under perceived payoffs. We consider two factors affecting such perceived payoffs: the population structure on which information and diseases spread, and individuals’ capabilities of processing information. They are modeled by network and prospect theory, respectively. Specifically, the population structure is described by a two-layer network composed of the decision-making network and the infection contagion network. We find network characteristics, such as network diameter, degree heterogeneity, and clustering, do not influence disease-behavior systems. On the other hand, taking local information from neighbors into account during the decision-making process and increasing the availability of vaccination raise the equilibrium level of vaccination. In addition, lowering the average degree of the infection contagion network (i.e., reducing physical contacts in the target population) suppresses the spread of diseases. All the three interventions reduce the costs of populations.
{"title":"Dynamic analysis and decision-making in disease-behavior systems with perceptions","authors":"Xue Feng, Long Wang, S. Levin","doi":"10.1109/CCDC.2019.8832524","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832524","url":null,"abstract":"Disease-behavior systems focus on the feedback loop between disease prevalence and individual vaccinating behavior: prevalent diseases stimulate individuals to vaccinate to avoid infection, high vaccination coverage mitigates the spread of diseases, then payoff-maximizers prefer not to vaccinate, which leads to the increase of non-vaccinators and facilitates disease outbreaks. In such coupled systems, individual vaccinating behavior usually depends on the perceived rather than real payoffs of infection and vaccination, which has not been fully explored. In this paper, we study the dynamics of disease-behavior systems and associated economic costs under perceived payoffs. We consider two factors affecting such perceived payoffs: the population structure on which information and diseases spread, and individuals’ capabilities of processing information. They are modeled by network and prospect theory, respectively. Specifically, the population structure is described by a two-layer network composed of the decision-making network and the infection contagion network. We find network characteristics, such as network diameter, degree heterogeneity, and clustering, do not influence disease-behavior systems. On the other hand, taking local information from neighbors into account during the decision-making process and increasing the availability of vaccination raise the equilibrium level of vaccination. In addition, lowering the average degree of the infection contagion network (i.e., reducing physical contacts in the target population) suppresses the spread of diseases. All the three interventions reduce the costs of populations.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"33 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":"115429228","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.2019.8832726
Wenjian Yan, Ke Wang, Ruifeng Li
Triangulation is a commonly used method for position estimation of mobile robots. In this work, we describe the triangulation algorithms in detail and analyze the error by establishing a Gaussian error model. We perform multiple triangulation algorithms using angular information of landmarks in one scan. A different approach is proposed to fuse the estimated values which is acquired from multiple triangulation algorithms. The proposed algorithm effectively improves the accuracy of position estimation based on triangulation and reduces the uncertainty of position.
{"title":"A Method for Position Estimation of Mobile Robot Based on Data Fusion","authors":"Wenjian Yan, Ke Wang, Ruifeng Li","doi":"10.1109/CCDC.2019.8832726","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832726","url":null,"abstract":"Triangulation is a commonly used method for position estimation of mobile robots. In this work, we describe the triangulation algorithms in detail and analyze the error by establishing a Gaussian error model. We perform multiple triangulation algorithms using angular information of landmarks in one scan. A different approach is proposed to fuse the estimated values which is acquired from multiple triangulation algorithms. The proposed algorithm effectively improves the accuracy of position estimation based on triangulation and reduces the uncertainty of position.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"4 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":"131730031","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.2019.8832890
Baoye Song, Gaoru Qi, Lin Xu
The unmanned aerial vehicles (UAVs) have been widely used in various fields in recent years, where the three-dimensional (3D) flight path planning is very important to realize the autonomous flight and complete the desired missions for the UAVs. Although the 3D flight path planning have become an active topic in the filed of the UAVs, there are still several critical problems to be further investigated to the authors’ knowledge. Motivated by the aforementioned considerations, the purpose of this survey is to present several representative approaches already proposed in the literature and provide some problems to be further investigated for the 3D flight path planning of the UAVs.
{"title":"A Survey of Three-Dimensional Flight Path Planning for Unmanned Aerial Vehicle","authors":"Baoye Song, Gaoru Qi, Lin Xu","doi":"10.1109/CCDC.2019.8832890","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832890","url":null,"abstract":"The unmanned aerial vehicles (UAVs) have been widely used in various fields in recent years, where the three-dimensional (3D) flight path planning is very important to realize the autonomous flight and complete the desired missions for the UAVs. Although the 3D flight path planning have become an active topic in the filed of the UAVs, there are still several critical problems to be further investigated to the authors’ knowledge. Motivated by the aforementioned considerations, the purpose of this survey is to present several representative approaches already proposed in the literature and provide some problems to be further investigated for the 3D flight path planning of the UAVs.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"106 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":"124216532","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.2019.8833176
Jinlei Ma, Z. Zhou, Bo Wang, Zhe An
In optical remote sensing images, many ships have very similar shapes and textures with backgrounds. In this case, it is very hard to accurately detect these ships. In this paper, we introduce generative adversarial networks (GANs) to perform hard ship detection. GANs consist of one generative network and one discriminator network. We take state-of-the-art object (ship) detection network Faster R-CNN as the generative network, which outputs the detection results as fake samples. The ground-truth ships in the input image are set as the real samples. The discriminator network is responsible for distinguishing between fake samples and real samples. The two networks are simultaneously trained. Through continuous adversarial training, the fake samples generated by the generative network can be very similar to the real samples, and the discriminator network would not correctly distinguish between fake samples and real samples. As a result, the ship detection network (generative network) correctly recognizes hard-detection ships, producing satisfactory detection results. What’s more, the discriminator network is only used in training process, and thus the proposed method not only improves detection accuracy, but also does not increase computational cost.
{"title":"Hard Ship Detection via Generative Adversarial Networks","authors":"Jinlei Ma, Z. Zhou, Bo Wang, Zhe An","doi":"10.1109/CCDC.2019.8833176","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833176","url":null,"abstract":"In optical remote sensing images, many ships have very similar shapes and textures with backgrounds. In this case, it is very hard to accurately detect these ships. In this paper, we introduce generative adversarial networks (GANs) to perform hard ship detection. GANs consist of one generative network and one discriminator network. We take state-of-the-art object (ship) detection network Faster R-CNN as the generative network, which outputs the detection results as fake samples. The ground-truth ships in the input image are set as the real samples. The discriminator network is responsible for distinguishing between fake samples and real samples. The two networks are simultaneously trained. Through continuous adversarial training, the fake samples generated by the generative network can be very similar to the real samples, and the discriminator network would not correctly distinguish between fake samples and real samples. As a result, the ship detection network (generative network) correctly recognizes hard-detection ships, producing satisfactory detection results. What’s more, the discriminator network is only used in training process, and thus the proposed method not only improves detection accuracy, but also does not increase computational cost.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"94 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":"122075130","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.2019.8833130
Xiaoyu Shi, Yuhua Cheng, Chun Yin, Han Shi, Xuegang Huang
In this paper, an actuator fault tolerant controller for the quadrotor UAV is designed. The new method is based on the adaptive RBF neural network and sliding mode control. The dynamic equations which includes external disturbances are constructed by Netwon-Euler theorem. External disturbances of unknown upper bound are approximated by RBF neural network. The adaptive strategy realized the on-line estimation of the actuator fault. The integrated FTC design approach guarantee the state variables converge to the desired values at limited time. The Lyapunov function prove that the system is global asymptotically stable. Futherfore, the backstepping sliding mode control technique alleviates the chattering phenomenon which result from switching law and solve the "explosion of complexity". The simulation results testified the effectiveness and robustness of the presented methodology for the quadrotor UAV.
{"title":"Actuator fault tolerant controlling using adaptive radical basis function neural network SMC for quadrotor UAV","authors":"Xiaoyu Shi, Yuhua Cheng, Chun Yin, Han Shi, Xuegang Huang","doi":"10.1109/CCDC.2019.8833130","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833130","url":null,"abstract":"In this paper, an actuator fault tolerant controller for the quadrotor UAV is designed. The new method is based on the adaptive RBF neural network and sliding mode control. The dynamic equations which includes external disturbances are constructed by Netwon-Euler theorem. External disturbances of unknown upper bound are approximated by RBF neural network. The adaptive strategy realized the on-line estimation of the actuator fault. The integrated FTC design approach guarantee the state variables converge to the desired values at limited time. The Lyapunov function prove that the system is global asymptotically stable. Futherfore, the backstepping sliding mode control technique alleviates the chattering phenomenon which result from switching law and solve the \"explosion of complexity\". The simulation results testified the effectiveness and robustness of the presented methodology for the quadrotor UAV.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"279 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120878874","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.2019.8832393
X. Ruan, Dingqi Ren, Xiao-qing Zhu, Jing Huang
Learning to navigate in an unknown environment is a crucial capability of mobile robot. Conventional method for robot navigation consists of three steps, involving localization, map building and path planning. However, most of the conventional navigation methods rely on obstacle map, and dont have the ability of autonomous learning. In contrast to the traditional approach, we propose an end-to-end approach in this paper using deep reinforcement learning for the navigation of mobile robots in an unknown environment. Based on dueling network architectures for deep reinforcement learning (Dueling DQN) and deep reinforcement learning with double q learning (Double DQN), a dueling architecture based double deep q network (D3QN) is adapted in this paper. Through D3QN algorithm, mobile robot can learn the environment knowledge gradually through its wonder and learn to navigate to the target destination autonomous with an RGB-D camera only. The experiment results show that mobile robot can reach to the desired targets without colliding with any obstacles.
{"title":"Mobile Robot Navigation based on Deep Reinforcement Learning","authors":"X. Ruan, Dingqi Ren, Xiao-qing Zhu, Jing Huang","doi":"10.1109/CCDC.2019.8832393","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832393","url":null,"abstract":"Learning to navigate in an unknown environment is a crucial capability of mobile robot. Conventional method for robot navigation consists of three steps, involving localization, map building and path planning. However, most of the conventional navigation methods rely on obstacle map, and dont have the ability of autonomous learning. In contrast to the traditional approach, we propose an end-to-end approach in this paper using deep reinforcement learning for the navigation of mobile robots in an unknown environment. Based on dueling network architectures for deep reinforcement learning (Dueling DQN) and deep reinforcement learning with double q learning (Double DQN), a dueling architecture based double deep q network (D3QN) is adapted in this paper. Through D3QN algorithm, mobile robot can learn the environment knowledge gradually through its wonder and learn to navigate to the target destination autonomous with an RGB-D camera only. The experiment results show that mobile robot can reach to the desired targets without colliding with any obstacles.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"64 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":"121099124","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.2019.8832906
Quancheng Cheng, Baoying Cui, Yanli Song, H. Ouyang
The problem of output tracking control for continuous nonlinear system is study in this thesis. The aim is to design a non-fragile tracking controller to guarantee a prescribed H∞ tracking performance. The T-S fuzzy model and the fuzzy observer are employed to solve this problem. The designed tracking controller and observer are proposed in terms of linear matrix inequalities(LMIs) by using a descriptor representation approach. Compared with the early studies, the designed tracking controller and observer gains can be solve without use the two-step procedures or other complex transform algorithms. Finally, a simulation experiment show the validity of the proposed method.
{"title":"Non-fragile Output Tracking Control for T-S Fuzzy Systems","authors":"Quancheng Cheng, Baoying Cui, Yanli Song, H. Ouyang","doi":"10.1109/CCDC.2019.8832906","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832906","url":null,"abstract":"The problem of output tracking control for continuous nonlinear system is study in this thesis. The aim is to design a non-fragile tracking controller to guarantee a prescribed H∞ tracking performance. The T-S fuzzy model and the fuzzy observer are employed to solve this problem. The designed tracking controller and observer are proposed in terms of linear matrix inequalities(LMIs) by using a descriptor representation approach. Compared with the early studies, the designed tracking controller and observer gains can be solve without use the two-step procedures or other complex transform algorithms. Finally, a simulation experiment show the validity of the proposed method.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"80 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":"128409254","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.2019.8832573
Guoliang Wang, Xiangzhou Gao
Under the network environment in which there may be subjected to packet dropouts and communication delays, the robust stabilization problem is solved for a class of nonlinear time-delay systems with both state and control inputs containing nonlinear perturbations. Under the assumption that the plant and the controller are connect through a network channel, we model the time-delay systems with nonlinearities and transform them into nonlinear time delay systems with time-varying input delays. By constructing a Lyapunov function making use of time-delay information, the problem of stabilization by static output-feedback controller is solved within the linear matrix inequalities (LMIs) framework, and better network control strategy can be obtained via our results.
{"title":"Robust stabilization for networked time-delay systems with nonlinearity","authors":"Guoliang Wang, Xiangzhou Gao","doi":"10.1109/CCDC.2019.8832573","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832573","url":null,"abstract":"Under the network environment in which there may be subjected to packet dropouts and communication delays, the robust stabilization problem is solved for a class of nonlinear time-delay systems with both state and control inputs containing nonlinear perturbations. Under the assumption that the plant and the controller are connect through a network channel, we model the time-delay systems with nonlinearities and transform them into nonlinear time delay systems with time-varying input delays. By constructing a Lyapunov function making use of time-delay information, the problem of stabilization by static output-feedback controller is solved within the linear matrix inequalities (LMIs) framework, and better network control strategy can be obtained via our results.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"35 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":"133255846","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.2019.8833259
Liu Tianyu, Yan Ruixin, Wei Guangrui, Sun Lei
When Dynamic Window Approach (DWA) is used in obstacle avoidance of blind-guiding robots, the contradiction which between the heading and velocity evaluation factors is not considered, resulting in, selecting the trajectory under certain road conditions, the not-timely collision avoidance, frequently direction changing, time-consuming planning and other issues in the planned path. To balance the relationship between the original three evaluation factors, the evaluation factor about the change of orientation is introduced into the function of path evaluation, which will suppress the excessive influence of a particular factor on the evaluation function under some specific circumstances, and to reduce unnecessary steering frequency of the robot. Experiments reveal that the actual required runtime of the planning path with the improved algorithm is reduced at average of 45.37% compared with that with the DWA algorithm, path planned with the improved algorithm can be planned advance to avoid obstacles with a smaller and continuous curvature. It can be obtained that the improved algorithm has a smoother trajectory and more timely collision avoidance, which can meet the comfort requirements of the blind-guiding robot’s users.
{"title":"Local Path Planning Algorithm for Blind-guiding Robot Based on Improved DWA Algorithm","authors":"Liu Tianyu, Yan Ruixin, Wei Guangrui, Sun Lei","doi":"10.1109/CCDC.2019.8833259","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833259","url":null,"abstract":"When Dynamic Window Approach (DWA) is used in obstacle avoidance of blind-guiding robots, the contradiction which between the heading and velocity evaluation factors is not considered, resulting in, selecting the trajectory under certain road conditions, the not-timely collision avoidance, frequently direction changing, time-consuming planning and other issues in the planned path. To balance the relationship between the original three evaluation factors, the evaluation factor about the change of orientation is introduced into the function of path evaluation, which will suppress the excessive influence of a particular factor on the evaluation function under some specific circumstances, and to reduce unnecessary steering frequency of the robot. Experiments reveal that the actual required runtime of the planning path with the improved algorithm is reduced at average of 45.37% compared with that with the DWA algorithm, path planned with the improved algorithm can be planned advance to avoid obstacles with a smaller and continuous curvature. It can be obtained that the improved algorithm has a smoother trajectory and more timely collision avoidance, which can meet the comfort requirements of the blind-guiding robot’s users.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"59 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":"126088755","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.2019.8833438
M. Abdelbaky, Xiangjie Liu, X. Kong
This study concentrates on the variable speed/pitch wind-turbines control for the overrated wind-speed. The pitch control is essential in this high wind-speed to adjust the rated output power. The key challenges of designing a pitch control for the wind-turbine are the constraints in the pitch-angle, wind turbine nonlinearities, the wind-speed variations, and the unmeasured states (unstructured model dynamics). From this point of view, this paper proposes constrained fuzzy-receding horizon pitch control to investigate the variable speed wind turbine performance. The proposed controller guarantees the nominal stability and converted to a simple online quadratic optimization problem which required less computational time to be solved. The proposed controller is compared with the gain scheduled-PI controller (which has been used abundantly in the wind-turbine industry) by applying the wind-turbine mathematical model. Additionally, a typical 5MW offshore wind-turbine simulator is employed to verify the results from the mathematical model. The results indicate the effectiveness of the proposed controller over the baseline controller.
{"title":"Wind Turbines Pitch Controller using Constrained Fuzzy-Receding Horizon Control","authors":"M. Abdelbaky, Xiangjie Liu, X. Kong","doi":"10.1109/CCDC.2019.8833438","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833438","url":null,"abstract":"This study concentrates on the variable speed/pitch wind-turbines control for the overrated wind-speed. The pitch control is essential in this high wind-speed to adjust the rated output power. The key challenges of designing a pitch control for the wind-turbine are the constraints in the pitch-angle, wind turbine nonlinearities, the wind-speed variations, and the unmeasured states (unstructured model dynamics). From this point of view, this paper proposes constrained fuzzy-receding horizon pitch control to investigate the variable speed wind turbine performance. The proposed controller guarantees the nominal stability and converted to a simple online quadratic optimization problem which required less computational time to be solved. The proposed controller is compared with the gain scheduled-PI controller (which has been used abundantly in the wind-turbine industry) by applying the wind-turbine mathematical model. Additionally, a typical 5MW offshore wind-turbine simulator is employed to verify the results from the mathematical model. The results indicate the effectiveness of the proposed controller over the baseline controller.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"74 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":"126171633","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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