Pub Date : 2020-07-01DOI: 10.23919/CCC50068.2020.9188757
Pu Zhang, Huifeng Xue, Shan Gao
This paper proposes a distributed adaptive control approach based on consensus theory so that a multi-agent formation can still complete the task despite the local fault of the leader for the multi-agent formation system. The controlled object consists of four agents that form a triangle formation system, where one agent acts as the vertex of the triangle, and the remaining agents act as followers in a line. Based on graph theory, the distributed adaptive updating of the agents’ local information parameters are conducted, and the distributed adaptive control law is used to supplement the influence of the leader’s fault in the multi-agent formation. According to the local information of adjacent agents, an overall distributed adaptive fault-tolerant control law is designed, and the stability of the designed controller is proved by constructing the Lyapunov function. Meanwhile, the relative distance error between the horizontal direction and longitudinal direction of the "leader-follower" converge to zero. The simulation results show that the proposed adaptive control approach has good robustness, which provides a theoretical basis for engineering practice.
{"title":"Fault-tolerant Control for Multi-agent with Actuator Fault","authors":"Pu Zhang, Huifeng Xue, Shan Gao","doi":"10.23919/CCC50068.2020.9188757","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9188757","url":null,"abstract":"This paper proposes a distributed adaptive control approach based on consensus theory so that a multi-agent formation can still complete the task despite the local fault of the leader for the multi-agent formation system. The controlled object consists of four agents that form a triangle formation system, where one agent acts as the vertex of the triangle, and the remaining agents act as followers in a line. Based on graph theory, the distributed adaptive updating of the agents’ local information parameters are conducted, and the distributed adaptive control law is used to supplement the influence of the leader’s fault in the multi-agent formation. According to the local information of adjacent agents, an overall distributed adaptive fault-tolerant control law is designed, and the stability of the designed controller is proved by constructing the Lyapunov function. Meanwhile, the relative distance error between the horizontal direction and longitudinal direction of the \"leader-follower\" converge to zero. The simulation results show that the proposed adaptive control approach has good robustness, which provides a theoretical basis for engineering practice.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125598277","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9188709
Taoran Yang, Jing Teng, Changling Li, Yizhan Feng
The increasing demand for wind power requires effective and reliable fault detection and diagnosis for wind turbines, which would reduce down-times and moderate repair costs. By adopting the Long Short Term Memory (LSTM) networks, we accurately predict the time-series data of proper functioning wind turbines based on the measured data. Compared with the traditional fault detection algorithm, our method could detect the faults more effectively. Simulation results verified that the proposed method could accurately and speedily detect the possible sensor faults and system faults defined in the benchmark model of wind turbines.
{"title":"Wind turbine fault detection and diagnosis using LSTM neural network","authors":"Taoran Yang, Jing Teng, Changling Li, Yizhan Feng","doi":"10.23919/CCC50068.2020.9188709","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9188709","url":null,"abstract":"The increasing demand for wind power requires effective and reliable fault detection and diagnosis for wind turbines, which would reduce down-times and moderate repair costs. By adopting the Long Short Term Memory (LSTM) networks, we accurately predict the time-series data of proper functioning wind turbines based on the measured data. Compared with the traditional fault detection algorithm, our method could detect the faults more effectively. Simulation results verified that the proposed method could accurately and speedily detect the possible sensor faults and system faults defined in the benchmark model of wind turbines.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772422","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9189079
Youcheng Chen, D. Niu, Qi Li, Xisong Chen, Li Ding, Jinbo Liu
The bridge crane system is widely used in the industrial production and its anti-sway positioning controls are crucial. In this paper, an anti-sway positioning control algorithm of unmanned crane is proposed based on ANFIS, which employs a structure similar to neural networks and can effectively calculate the optimal parameters of the membership function through the back propagation algorithm and the least square algorithm. The experimental results show that the proposed algorithm can achieve high positioning accuracy under the condition of a certain range of rope length. The load sway angle is small when the target position is reached.
{"title":"An Anti-sway Positioning Algorithm of Unmanned Crane Based on ANFIS","authors":"Youcheng Chen, D. Niu, Qi Li, Xisong Chen, Li Ding, Jinbo Liu","doi":"10.23919/CCC50068.2020.9189079","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9189079","url":null,"abstract":"The bridge crane system is widely used in the industrial production and its anti-sway positioning controls are crucial. In this paper, an anti-sway positioning control algorithm of unmanned crane is proposed based on ANFIS, which employs a structure similar to neural networks and can effectively calculate the optimal parameters of the membership function through the back propagation algorithm and the least square algorithm. The experimental results show that the proposed algorithm can achieve high positioning accuracy under the condition of a certain range of rope length. The load sway angle is small when the target position is reached.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"74 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121949298","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9189526
Zhigang Zhou, Xinwei Chen, Ruifeng Li, Xiao‐Ning Shi, K. Wen
This paper addresses the tracking control problem for uncertain Euler-Lagrange system with time-varying output constraints in an environment containing obstacles. First, a novel log-type attractive potential field is utilized to describe the trajectory tracking task with time-varying constraints, and a bounded artificial potential field is established to describe the obstacle avoidance task. Then, by incorporating the two artificial potential fields (APFs) into the dynamic surface control, a neuro-adaptive tracking control is designed for the uncertain Euler-Lagrange system, which can ensure the system to fulfill the trajectory track task within time-varying limit range while avoiding obstacles. Because the obstacle avoidance task has a higher priority, the proposed control scheme can also guarantee the obstacle avoiding task can be fulfilled first when it is conflicted with the trajectory tracking task. Numerical simulations are provided to demonstrate the efficacy of the control strategy.
{"title":"Neuro-adaptive tracking control for uncertain Euler-Lagrange systems with time-varying output constraints and obstacle avoidance","authors":"Zhigang Zhou, Xinwei Chen, Ruifeng Li, Xiao‐Ning Shi, K. Wen","doi":"10.23919/CCC50068.2020.9189526","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9189526","url":null,"abstract":"This paper addresses the tracking control problem for uncertain Euler-Lagrange system with time-varying output constraints in an environment containing obstacles. First, a novel log-type attractive potential field is utilized to describe the trajectory tracking task with time-varying constraints, and a bounded artificial potential field is established to describe the obstacle avoidance task. Then, by incorporating the two artificial potential fields (APFs) into the dynamic surface control, a neuro-adaptive tracking control is designed for the uncertain Euler-Lagrange system, which can ensure the system to fulfill the trajectory track task within time-varying limit range while avoiding obstacles. Because the obstacle avoidance task has a higher priority, the proposed control scheme can also guarantee the obstacle avoiding task can be fulfilled first when it is conflicted with the trajectory tracking task. Numerical simulations are provided to demonstrate the efficacy of the control strategy.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121956979","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9188842
Yikai Zhang, Bailing Tian, Hongming Chen
This paper proposes a relative localization algorithm for Multi-UAV system, in which each agent is able to estimate the relative position of its neighbor based on Ultra-wideband measurement and visual odometry information exchanged. The relative localization algorithm consists of two parts. Visual odometry pre-process part fuses the IMU data and radar altimeter data to correct visual odometry error and reach a higher update rate to ensure flight smoothly and a better state estimation. Using the UWB measurement and information exchanged, each agent constructs a graph to solve relative localization problem in sliding window. Finally, experimental results are presented to corroborate the effectiveness of our proposed relative localization algorithm.
{"title":"Ultra-wideband and Visual Odometry Based Relative Localization for Multi-UAV System","authors":"Yikai Zhang, Bailing Tian, Hongming Chen","doi":"10.23919/CCC50068.2020.9188842","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9188842","url":null,"abstract":"This paper proposes a relative localization algorithm for Multi-UAV system, in which each agent is able to estimate the relative position of its neighbor based on Ultra-wideband measurement and visual odometry information exchanged. The relative localization algorithm consists of two parts. Visual odometry pre-process part fuses the IMU data and radar altimeter data to correct visual odometry error and reach a higher update rate to ensure flight smoothly and a better state estimation. Using the UWB measurement and information exchanged, each agent constructs a graph to solve relative localization problem in sliding window. Finally, experimental results are presented to corroborate the effectiveness of our proposed relative localization algorithm.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122010948","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9188594
Wenhao Ma, Rui Huang, Qiming Chen, Guangkui Song, Cong Li
Lower limb exoskeleton robot is widely used in clinical rehabilitation training and daily walking for paraplegia patients. However, most of lower extremity exoskeleton products use fixed gait and speed, making them limited in use. Therefore, this paper proposes a parametric gait model for lower limb exoskeleton gait planning, which is based on the dynamic movement primitives method. By learning the characteristics of the sample curves of hip and knee joints at different velocities, the model can output the curve of hip and knee joints under continuous velocity variation. Thus, the lower limb exoskeleton is given an anthropomorphic variable gait which would enhance its dynamic performance and broaden the application scenarios.
{"title":"Dynamic Movement Primitives based Parametric Gait Model for Lower Limb Exoskeleton","authors":"Wenhao Ma, Rui Huang, Qiming Chen, Guangkui Song, Cong Li","doi":"10.23919/CCC50068.2020.9188594","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9188594","url":null,"abstract":"Lower limb exoskeleton robot is widely used in clinical rehabilitation training and daily walking for paraplegia patients. However, most of lower extremity exoskeleton products use fixed gait and speed, making them limited in use. Therefore, this paper proposes a parametric gait model for lower limb exoskeleton gait planning, which is based on the dynamic movement primitives method. By learning the characteristics of the sample curves of hip and knee joints at different velocities, the model can output the curve of hip and knee joints under continuous velocity variation. Thus, the lower limb exoskeleton is given an anthropomorphic variable gait which would enhance its dynamic performance and broaden the application scenarios.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122276577","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 order to realize large-scale distributed inverter air conditioning load participating in demand response, this paper proposes the multi-agent consensus control algorithm to meet the requirements of accurate load control of residential air conditioning resources. Based on the concept of human body comfort index in meteorology, this paper takes comfort index ratio as a consensus variable to reduce the load of inverter air conditioning group by changing the set temperature of air conditioner. The algorithm can reduce the data traffic through the information interaction between adjacent agents, so it can successfully complete the load reduction instructions issued by the scheduling center. Case simulation and analysis show the effectiveness of the proposed strategy.
{"title":"Multi-Agent Consensus Control of Distributed Inverter Air Conditioning Load Based on the Demand Response","authors":"Peng Liu, Lida Chen, Tengxiao Ma, Xingzhen Bai, Hongxiang Xu","doi":"10.23919/CCC50068.2020.9189633","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9189633","url":null,"abstract":"In order to realize large-scale distributed inverter air conditioning load participating in demand response, this paper proposes the multi-agent consensus control algorithm to meet the requirements of accurate load control of residential air conditioning resources. Based on the concept of human body comfort index in meteorology, this paper takes comfort index ratio as a consensus variable to reduce the load of inverter air conditioning group by changing the set temperature of air conditioner. The algorithm can reduce the data traffic through the information interaction between adjacent agents, so it can successfully complete the load reduction instructions issued by the scheduling center. Case simulation and analysis show the effectiveness of the proposed strategy.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127939006","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9189307
Jiashun Shi, Jin Chen, Wen Qi
This paper applies the pan-Boolean PID control algorithm to the stepper motor servo control system. The mathematical simulation control model of the step-motor servo control system [l]is established in the MATALB / SIMULINK environment. Compare the output effect in the stepper motor servo controller. Analysis of simulation model results shows that compared with traditional PID control, pan-Boolean PID control has good control effects such as fast response speed, small overshoot, short adjustment time, and strong robustness. In order to verify the general practicability of the stepper motor servo controller based on the pan-Boolean PID control algorithm, a stepper motor servo controller based on a dedicated control and control chip is designed in this paper. The stepping servo controller designed in this paper has basic functionality. The stepping servo controller can meet the development needs of modem industry, and has certain practical significance for the theoretical research and production practice of the servo controller.
{"title":"Research on Stepper Motor Servo Controller Based on Pan-Boolean PID Control","authors":"Jiashun Shi, Jin Chen, Wen Qi","doi":"10.23919/CCC50068.2020.9189307","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9189307","url":null,"abstract":"This paper applies the pan-Boolean PID control algorithm to the stepper motor servo control system. The mathematical simulation control model of the step-motor servo control system [l]is established in the MATALB / SIMULINK environment. Compare the output effect in the stepper motor servo controller. Analysis of simulation model results shows that compared with traditional PID control, pan-Boolean PID control has good control effects such as fast response speed, small overshoot, short adjustment time, and strong robustness. In order to verify the general practicability of the stepper motor servo controller based on the pan-Boolean PID control algorithm, a stepper motor servo controller based on a dedicated control and control chip is designed in this paper. The stepping servo controller designed in this paper has basic functionality. The stepping servo controller can meet the development needs of modem industry, and has certain practical significance for the theoretical research and production practice of the servo controller.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121453415","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9188453
Qing Peng, Zhiwei Liu
Short-term residential load forecasting (STRLF) is the crucial step of customer side demand response (CSDR) that is mainly applied to peak cut through the adjustment of electricity price. Compared with load forecasting of high voltage level, STRLF is a more challenging task due to the high volatility and randomness of load. Most studies focus on STRLF using traditional machine learning and recursive neural network technology, which are difficult to maintain long-term load memory. Temporal Convolutional Networks (TCN), a deep learning method, is put forward to predict residential load which can not only keep the load memory longer, but also process the load information in parallel. Based on AMPds2 smart meter data set, experiments show that the proposed method has a great advantage over the state-of-the-art methods.
{"title":"Short-Term Residential Load Forecasting Based on Smart Meter Data Using Temporal Convolutional Networks","authors":"Qing Peng, Zhiwei Liu","doi":"10.23919/CCC50068.2020.9188453","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9188453","url":null,"abstract":"Short-term residential load forecasting (STRLF) is the crucial step of customer side demand response (CSDR) that is mainly applied to peak cut through the adjustment of electricity price. Compared with load forecasting of high voltage level, STRLF is a more challenging task due to the high volatility and randomness of load. Most studies focus on STRLF using traditional machine learning and recursive neural network technology, which are difficult to maintain long-term load memory. Temporal Convolutional Networks (TCN), a deep learning method, is put forward to predict residential load which can not only keep the load memory longer, but also process the load information in parallel. Based on AMPds2 smart meter data set, experiments show that the proposed method has a great advantage over the state-of-the-art methods.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121625217","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 : 2020-07-01DOI: 10.23919/CCC50068.2020.9188393
Mengge Zhang, Jie Li, Xiangke Wang
The area coverage problem is an important issue because it can minimize uncertainty in a complex and unknown environment. This paper adopts a distributed anti-flocking algorithm inspired by the social behavior of solitary animals, which enables self-organized collaboration of multiple unmanned aerial vehicles (multi-UAVs) to achieve effective coverage of the mission area. The designed area coverage map represents the historical coverage information of each unmanned aerial vehicle (UAV). According to the rules of collision avoidance, decentering, and selfishness in the distributed anti-flocking algorithm, the UAVs are guided to move towards the direction that maximizing the coverage area and try to reduce the overlap of coverage region as well. Simulations show that the algorithm can achieve approximate full coverage of the task area and has good scalability, adaptability, and robustness.
{"title":"Distributed anti-flocking method for area coverage of multiple unmanned aerial vehicles","authors":"Mengge Zhang, Jie Li, Xiangke Wang","doi":"10.23919/CCC50068.2020.9188393","DOIUrl":"https://doi.org/10.23919/CCC50068.2020.9188393","url":null,"abstract":"The area coverage problem is an important issue because it can minimize uncertainty in a complex and unknown environment. This paper adopts a distributed anti-flocking algorithm inspired by the social behavior of solitary animals, which enables self-organized collaboration of multiple unmanned aerial vehicles (multi-UAVs) to achieve effective coverage of the mission area. The designed area coverage map represents the historical coverage information of each unmanned aerial vehicle (UAV). According to the rules of collision avoidance, decentering, and selfishness in the distributed anti-flocking algorithm, the UAVs are guided to move towards the direction that maximizing the coverage area and try to reduce the overlap of coverage region as well. Simulations show that the algorithm can achieve approximate full coverage of the task area and has good scalability, adaptability, and robustness.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132392513","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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