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2021 40th Chinese Control Conference (CCC)最新文献

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A Novel Constructive Heuristic for Flowshop Group Scheduling Problems to Minimize Total Flow Time 最小化总流时间的流水车间群调度问题的一种新的建设性启发式算法
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9549650
Xuan He, Yu-Fan Liu, Q. Pan, Yang Yu, Yuan-Zhen Li
{"title":"A Novel Constructive Heuristic for Flowshop Group Scheduling Problems to Minimize Total Flow Time","authors":"Xuan He, Yu-Fan Liu, Q. Pan, Yang Yu, Yuan-Zhen Li","doi":"10.23919/CCC52363.2021.9549650","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9549650","url":null,"abstract":"Due to the extensive applications of the flowshop sequence-dependent group scheduling problem(FSDGSP), especially in the manufacturing industry, there has been a growing interest in the research of it. In this paper, a constructive heuristic called JPALRx is proposed for solving FSDGSP with total flow time criterion. In the JPALRx, a sequence of part families is determined by a jigsaw puzzle inspired algorithm considering major family setup times. Afterwards, a job sequence within each part family is obtained by using a heuristic algorithm called LRx. Furthermore, an insert operator based on family is used to further improve the quality of the solution obtained. The experimental results demonstrate the effectiveness and efficiency of JPALRx.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114980074","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}
引用次数: 0
A Velocity Tracking Control Method for Electric Vehicle Based on Model Predictive Control 基于模型预测控制的电动汽车速度跟踪控制方法
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9550199
Shanhao Feng, Liling Ma, Tao Chen, Shou-kun Wang, Junzheng Wang
{"title":"A Velocity Tracking Control Method for Electric Vehicle Based on Model Predictive Control","authors":"Shanhao Feng, Liling Ma, Tao Chen, Shou-kun Wang, Junzheng Wang","doi":"10.23919/CCC52363.2021.9550199","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9550199","url":null,"abstract":"For the velocity tracking control of electric vehicle, the classical control algorithm is difficult to obtain high precision. Modern control algorithms can improve the control accuracy but they require accurate vehicle dynamics modeling. For this situation,a hierarchical model predictive control(MPC) strategy is proposed. Compared with traditional vehicles, electric vehicles are driven by motors, which are more suitable for model predictive control.In the proposed strategy, the controller can adaptively adjust the acceleration to track the expected velocity without accurate vehicle model.An upper MPC controller is designed to uses the expected velocity and the actual velocity to calculate the expected acceleration. The lower controller establishes the vehicle inverse dynamics model to calculate the expected opening degree of the accelerator pedal and the braking pressure through the Inverse dynamics model of vehicle. Simulation results demonstrate that the the controller has a fast response and accurate tracking performance without overshoot.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363963","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}
引用次数: 0
Adaptive Backstepping Path Following Control of Autonomous Ground Vehicles with Sideslip Effects 具有侧滑效应的自动驾驶地面车辆自适应后退路径跟踪控制
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9549584
Surui Li, Heng Wang, Wei Quan, Qing Li, Xuanzhi Wang
{"title":"Adaptive Backstepping Path Following Control of Autonomous Ground Vehicles with Sideslip Effects","authors":"Surui Li, Heng Wang, Wei Quan, Qing Li, Xuanzhi Wang","doi":"10.23919/CCC52363.2021.9549584","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9549584","url":null,"abstract":"This paper presents an adaptive backstepping path tracking controller design approach of autonomous ground vehicles (AGVs). The path tracking model of the AGV is converted into a nonlinear system through chain form transformation, whose states are estimated by an adaptive observer considering both actuator effectiveness loss and tire sideslip effects. A backstepping control strategy is then proposed which guarantees that the closed-loop system is stable and system signals are uniformly ultimately bounded. Simulation shows the advantage of the control method proposed.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115691246","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}
引用次数: 0
Simultaneous estimation of unknown input and state for measurement delay systems based on Kalman filter 基于卡尔曼滤波的测量延迟系统未知输入和状态的同时估计
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9550718
Ling Gao, Y. Guan, Xinmin Song
{"title":"Simultaneous estimation of unknown input and state for measurement delay systems based on Kalman filter","authors":"Ling Gao, Y. Guan, Xinmin Song","doi":"10.23919/CCC52363.2021.9550718","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9550718","url":null,"abstract":"In this paper, for the linear discrete-time system with measurement delay, a research scheme is proposed to take the unknown input and state estimation algorithm as the limit of Kalman filter. Firstly, the existing recursive filters of state and input are refined and summarized. Secondly, under the assumption that the unknown input is Gaussian white noise, the Kalman filter theory is used to design recursive filter for unknown input and state. Then, under the specific condition that the variance of unknown input tends to infinity, it is proved that the simultaneous estimation of unknown input and state is a standard Kalman filtering algorithm with specific unknown input model. Finally, a numerical example is given to prove the effectiveness of the research scheme.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123138075","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}
引用次数: 0
Path Planning for Mobile Robots with Courteous Behaviors in Domestic Environments 家庭环境中具有礼貌行为的移动机器人路径规划
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9550586
Hao Yu, Zongxin Kuang, Fengchi Sun, Jing Yuan, MingMing Liu, Maoqiang Xie
{"title":"Path Planning for Mobile Robots with Courteous Behaviors in Domestic Environments","authors":"Hao Yu, Zongxin Kuang, Fengchi Sun, Jing Yuan, MingMing Liu, Maoqiang Xie","doi":"10.23919/CCC52363.2021.9550586","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9550586","url":null,"abstract":"Along with the development of artificial intelligence, it has become a trend for mobile robots to serve and coexist with humans in domestic environments. It is significant to research path planning and make robots realize courteous behavioral patterns. These patterns can make robots avoid moving obstacles more regularly, and promote robots to get along with humans better. In this paper, we analyze common path planning algorithms for mobile robots. In order to realize courteous behaviors of mobile robots, we consider global path planning and local path planning comprehensively. We propose a method combining the smoothing ARA* algorithm for global path planning and the improved DWA algorithm for local path planning. The simulated experiments verify the effectiveness of the proposed algorithm.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668780","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}
引用次数: 2
Finite-Time State Estimation for Discrete-Time Nonlinear Singularly Perturbed Complex Networks under New Event-Triggered Mechanism† 新的事件触发机制下离散非线性奇摄动复杂网络的有限时间状态估计[j]
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9550566
Chao Yang, Xiongbo Wan
{"title":"Finite-Time State Estimation for Discrete-Time Nonlinear Singularly Perturbed Complex Networks under New Event-Triggered Mechanism†","authors":"Chao Yang, Xiongbo Wan","doi":"10.23919/CCC52363.2021.9550566","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9550566","url":null,"abstract":"This paper investigates the finite-time state estimation problem for a class of discrete-time nonlinear singularly perturbed complex networks under a new dynamic event-triggered mechanism (DETM). This new DETM is devised to adjust the date packet transmissions flexibly with hope to save network resources. By constructing a new Lyapunov function dependent on the information of the singular perturbation parameter (SPP) and DETM, a sufficient condition is derived which ensures that the error dynamics of state estimation is finite-time stable. The parameters of the state estimator are given by means of the solutions to several matrix inequalities and the upper bound of the SPP can be evaluated simultaneously. The effectiveness of the designed state estimator is demonstrated by a numerical example.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125234205","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}
引用次数: 0
Tracking control for fractional-order uncertain systems based on the indirect Lyapunov method 基于间接李雅普诺夫方法的分数阶不确定系统跟踪控制
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9549455
Rui-Juan Liu, Zhiqiang Qin, Zhuo‐Yun Nie
{"title":"Tracking control for fractional-order uncertain systems based on the indirect Lyapunov method","authors":"Rui-Juan Liu, Zhiqiang Qin, Zhuo‐Yun Nie","doi":"10.23919/CCC52363.2021.9549455","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9549455","url":null,"abstract":"Aiming at a class of uncertain fractional-order systems, the idea of equivalent-input-disturbance is applied to design the tracking control of the system. Firstly, the state space model of the system is established, and then the indirect Lyapunov method is used to analyze the stability of the system and design the parameters. Sufficient conditions for stability are given in the form of linear matrix inequalities. Finally, numerical examples show that the method has good tracking control and disturbance suppression performance.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116705847","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}
引用次数: 0
A Deep Neural Networks Based on Multi-task Learning and Its Application 基于多任务学习的深度神经网络及其应用
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9549842
Mengru Zhao, Yuxian Zhang, Likui Qiao, Deyuan Sun
{"title":"A Deep Neural Networks Based on Multi-task Learning and Its Application","authors":"Mengru Zhao, Yuxian Zhang, Likui Qiao, Deyuan Sun","doi":"10.23919/CCC52363.2021.9549842","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9549842","url":null,"abstract":"With the development of machine learning, the deep neural network has achieved excellent performance. However, the learning of deep neural network often needs a large number of data and the independent learning of a single task tends to ignore the information from other tasks, resulting in redundant training and the cost of learning resources. In order to solve these problems, we introduce the deep neural network based on multi-task learning model. We introduce the structure of the multi-tasking learning model in detail, and use demographic information to prove the effectiveness of the model. Finally deep neural network based on multi-task learning framework is adapted to builds a normal behavior model for wind turbine generator in which each subspace of operating condition are taken as a task. The operating data comes from Liaoning wind farm in northeast China are used to verify the proposed method. The results indicate the subspace division of different operating condition benefits to improve the accuracy of normal behavior model of wind turbine generator, and multi-task learning is suitable to deal with the integrate subspace model.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116792158","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}
引用次数: 1
A Sensor Selection Method for Nonlinear Localization in the Presence of Sensor Errors 存在传感器误差的非线性定位传感器选择方法
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9550166
Wen Ma, Hongyan Zhu
{"title":"A Sensor Selection Method for Nonlinear Localization in the Presence of Sensor Errors","authors":"Wen Ma, Hongyan Zhu","doi":"10.23919/CCC52363.2021.9550166","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9550166","url":null,"abstract":"This paper considers the localization problem of a mobile source based on time difference of arrival (TDOA) measurements and angle of arrival (AOA) measurements in the presence of random noises in both measurements and sensor location. We propose a sensor selection mechanism which aims to choose a subset of sensors to implement the multi-sensor passive localization. We use the covariance of the improved unscented Kalman filter (UKF) as a cost function where the dynamic model is augmented by incorporating the sensor positions into the state vector. Correspondingly, the number of sigma points in the improved UKF is also enlarged. Although the proposed method requires higher computational complexity, the selected subset achieves a better estimation performance in comparison with that of the linearization method EKF or classical UKF method which ignores the sensor position uncertainties. And the CEO (cross entropy optimization) is employed to solve the resulting complex combinatorial optimization model. Simulation experiments are conducted and simulation results demonstrate the efficiency of the proposed sensor selection scheme for multi-sensor passive localization.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116894302","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}
引用次数: 0
Optimal Scheduling of Microgrid with Variable Current for Energy Storage 微电网变电流储能优化调度
2021 40th Chinese Control Conference (CCC) Pub Date : 2021-07-26 DOI: 10.23919/CCC52363.2021.9549479
Qiang Wang, Xiaowen Li, Ruyi Zhang, Zhiyuan Qi
{"title":"Optimal Scheduling of Microgrid with Variable Current for Energy Storage","authors":"Qiang Wang, Xiaowen Li, Ruyi Zhang, Zhiyuan Qi","doi":"10.23919/CCC52363.2021.9549479","DOIUrl":"https://doi.org/10.23919/CCC52363.2021.9549479","url":null,"abstract":"The energy storage unit plays an important role in balancing power fluctuations of microgrid. Unreasonable battery scheduling will cause more life loss and increase the replacement cost of the battery. Therefore, prolonging the life of the battery becomes one of the key factors to improve the microgrid economy. According to terminal voltage characteristics of lithium batteries in the process of charging and discharging, this paper proposes an optimal scheduling method of isolated microgrid with variable current for energy storage, in order to reduce the damage of battery life caused by the polarization and over-discharge phenomenon. According to the relationship between the state of charge (SOC) and the terminal voltage of the battery, the charging or discharging current in different SOC is dynamically adjusted during the scheduling process. In addition, a scheduling strategy coordinating the power output of the battery and the micro gas turbine (MGT) is proposed to reduce the mechanical wear and tear of the MGT as well as decrease the life loss of the battery. The results of simulation show that the proposed microgrid scheduling strategy with variable current for energy storage can effectively extend the battery life and reduce the operation cost of the microgrid.","PeriodicalId":306184,"journal":{"name":"2021 40th Chinese Control Conference (CCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117058383","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}
引用次数: 0
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