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2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)最新文献

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Formation control method based on guidance and LADRC for underactuated USVs 欠驱动无人潜航器基于制导和LADRC的编队控制方法
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166575
Yuhe Ma, Chaofang Hu, Yiyi Xiang
{"title":"Formation control method based on guidance and LADRC for underactuated USVs","authors":"Yuhe Ma, Chaofang Hu, Yiyi Xiang","doi":"10.1109/DDCLS58216.2023.10166575","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166575","url":null,"abstract":"In this work, to deal with the formation problem of underactuated Unmanned Surface Vehicles (USVs) with obstacle avoidance, the synthesized formation control strategy based on Line-of-Sight (LOS) guidance law and the Linear Active Disturbance Rejection Control (LADRC) method is proposed. Firstly, the mathematical model of the USV is established. Secondly, the formation controller is designed according to the LOS guidance law. Then the Artificial Potential Field (APF) method is introduced to solve the obstacle avoidance problem. Moreover, the LADRC method is used to realize the motion control. The simulation results show that the formation control method works well.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127570509","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
Dynamic Path Planning of UAV Based on KF-RRT Algorithm 基于KF-RRT算法的无人机动态路径规划
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166695
Hang Yan, Xingjian Fu
{"title":"Dynamic Path Planning of UAV Based on KF-RRT Algorithm","authors":"Hang Yan, Xingjian Fu","doi":"10.1109/DDCLS58216.2023.10166695","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166695","url":null,"abstract":"For the dynamic path planning of UAV, an algorithm based on Kalman Filter and improved Rapid-exploration Random Tree (KF-RRT) is proposed. Firstly, on the basis of the RRT algorithm, the weight coefficient of the target area trend is added, which reduces the time of UAV path planning. Secondly, the prediction function of Kalman Filter is added to predict the motion trajectory of dynamic obstacles in advance. Then, B-spline curve is used for smoothing to plan the feasible path of UAV. Finally, the KF-RRT algorithm in this paper is compared with other RRT algorithms by simulation, which shows that the proposed algorithm is more suitable for the dynamic path planning of UAV.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126550757","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
Event-triggered Extended Kalman Filter for UAV Monitoring System 无人机监控系统的事件触发扩展卡尔曼滤波
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167412
Yunge Zang, Yan Li, Yuting Duan, Xiangyu Li, Xin Chang, Zhuguo Li
{"title":"Event-triggered Extended Kalman Filter for UAV Monitoring System","authors":"Yunge Zang, Yan Li, Yuting Duan, Xiangyu Li, Xin Chang, Zhuguo Li","doi":"10.1109/DDCLS58216.2023.10167412","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167412","url":null,"abstract":"To facilitate ground station monitoring and command uploading, unmanned aerial vehicles (UAVs) need to frequently exchange individual state data between units. However, this results in a significant usage of communication bandwidth. To address this issue, on the basis of an event-triggered strategy, this paper proposes an Extended Kalman Filter (EKF). aimed at reducing the communication burden of UAVs while maintaining high accuracy. Specifically, a state measurement triggered by an event is selected for filtering only if it contains innovation, thereby reducing the amount of data that needs to be communicated. Since UAV systems are nonlinear, EKF is adopted to fully utilize the information obtained from event-triggered strategies, thereby enhancing the estimation performance. In this paper, a physical UAV was used to verify the proposed algorithm, and it proved to have robust dynamic performance and to effectively reduce the communication rate.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130700533","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 Data-driven Physical Mechanism Modeling Method for the Spin-Exchange Relaxation-Free Comagnetometer 一种数据驱动的自旋交换无松弛磁强计物理机制建模方法
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167072
Fen Li, Zhuo Wang, Min Zhang, Ruigang Wang, Bodong Qin, Yanchao Chai
{"title":"A Data-driven Physical Mechanism Modeling Method for the Spin-Exchange Relaxation-Free Comagnetometer","authors":"Fen Li, Zhuo Wang, Min Zhang, Ruigang Wang, Bodong Qin, Yanchao Chai","doi":"10.1109/DDCLS58216.2023.10167072","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167072","url":null,"abstract":"The Spin-Exchange Relaxation-Free Comagnetometer (SERFCM) is a new quantum instrument with ultra-high accuracy. Normally, the atomic ensembles of SERFCM operate in an open-loop state, which is not conducive to long-term high-precision measurements. In order to realize closed-loop control of its atomic polarization state, it is necessary to model and analyze the dynamic characteristics of the SERFCM system. In this paper, a Data-driven physical mechanism (DDPM) modeling method is proposed to realize the modeling of the SERFCM, a multi-input multi-output system. First, the state space equations of the SERFCM are established based on the Bloch equation, which are transformed into a discrete transfer function matrix. Then, based on the criterion of least variance in estimation, we realize the modeling of the discrete transfer function matrix using the excitation input data, the measured output data, and the estimated output data. Finally, the simulation results of modeling under different longitudinal magnetic fields confirm the validity of the proposed method. This work enables the online modeling of SERFCM system and facilitates the analysis of the effects of various parameters on the dynamic characteristics.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125239796","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 control of stochastic power system based on braking resistance 基于制动阻力的随机电力系统最优控制
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167145
X. Lin, Qi Wang, Yinsheng Luo, Changchun Cai
{"title":"Optimal control of stochastic power system based on braking resistance","authors":"X. Lin, Qi Wang, Yinsheng Luo, Changchun Cai","doi":"10.1109/DDCLS58216.2023.10167145","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167145","url":null,"abstract":"How to suppress the adverse effects of the uncertainty of renewable energy on power systems has always been a major technical requirement for power system operation, which has not been sufficiently considered in the traditional power system controller. Therefore, it is necessary to study the power system control under stochastic disturbances. In this paper, a controlled single-machine infinite-bus system model is established based on the stochastic averaging method of quasi-Hamiltonian systems, and a one-dimensional diffusion equation based on energy function with control item is obtained. According to the stochastic optimal control theory, the optimal control law of the system is obtained from the diffusion equation with the maximum reliability of the bounded fluctuation of the system as the control target. The effectiveness of the control method is verified by simulation.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130741389","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
Online Parameter Identification for Fractional Order Model of Lithium Ion Battery via Adaptive Genetic Algorithm 基于自适应遗传算法的锂离子电池分数阶模型参数在线辨识
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166251
Bingjun Guo, Huanli Sun, Z. Zhao, Yixin Liu
{"title":"Online Parameter Identification for Fractional Order Model of Lithium Ion Battery via Adaptive Genetic Algorithm","authors":"Bingjun Guo, Huanli Sun, Z. Zhao, Yixin Liu","doi":"10.1109/DDCLS58216.2023.10166251","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166251","url":null,"abstract":"In order to overcome the shortcomings of the equivalent circuit model and the electrochemical model, a fractional impedance model is established based on the electrochemical impedance spectrum data, and the polarization effect is described in a simple and meaningful way using fractional elements. In this paper, we propose an online parameter identification method for fractional order model (FOM) of lithium ion battery, where an adaptive genetic algorithm is designed to estimation unknown parameters. To this end, an FOM is constructed by using the Grünwald-Letnikov (GL) definition. Then, an unscented kalman filter (UKF) method is adopted to estimate the internal model states. Based on the obtained states, an adaptive genetic algorithm (AGA) is designed to online identify the unknown parameters. Finally, comprehensive experimental verification results are provided to show the effectiveness of the proposed methods.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130916049","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 robust variable projection algorithm for RBF-AR model RBF-AR模型的鲁棒变量投影算法
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166930
Yuexin She, Guang-yong Chen, Min Gan
{"title":"A robust variable projection algorithm for RBF-AR model","authors":"Yuexin She, Guang-yong Chen, Min Gan","doi":"10.1109/DDCLS58216.2023.10166930","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166930","url":null,"abstract":"The radial basis function network-based autoregressive (RBF-AR) model is a powerful statistical model which can be expressed as a linear combination of nonlinear functions and frequently appears in a wide range of application fields. Variable projection algorithm is designed for solving smooth separable optimization problems with least squares form and has been used as an efficient tool for the identification of RBF-AR model. However, in real applications, the observations are usually disturbed by non-Gaussian noise or contain outliers. This often leads to nonlinear regression problems. Since there are both linear and nonlinear parameters in such problems, how to optimize such models is still challenging. In this paper, we design a robust variable projection algorithm for the identification of RBF-AR model. The proposed method takes into account the coupling of the linear and nonlinear parameters of RBF-AR model, which eliminates the linear parameters by solving a linear programming and optimizes the reduced function that only contains nonlinear parameters. Numerical results on RBF-AR model to synthetic data and real-world data confirm the effectiveness of the proposed algorithm.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130932367","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 repetitive control for a class of uncertain nonlinear systems with input delay 一类输入时滞不确定非线性系统的自适应重复控制
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166609
Yongbo Sun, Lan Zhou, Chengyang Li, Qin Yang, Wenbin Xiao
{"title":"Adaptive repetitive control for a class of uncertain nonlinear systems with input delay","authors":"Yongbo Sun, Lan Zhou, Chengyang Li, Qin Yang, Wenbin Xiao","doi":"10.1109/DDCLS58216.2023.10166609","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166609","url":null,"abstract":"An adaptive repetitive control method is presented in this paper for a class of uncertain nonlinear systems with input delay and mismatched disturbances. The original tracking problem of the uncertain nonlinear system is divided into two subproblems: repetitive control problem of a primary linear time-invariant (LTI) system and robust stabilization problem of a secondary nonlinear system with input delay and mismatched disturbances. Repetitive control is used in the primary LTI system to handle the periodic signal, where a slight correction to amount of the time delay of the repetitive controller is introduced, leading to a significant improvement in steady-state tracking performance. Adaptive backstepping control is used in the secondary nonlinear system to deal with structural uncertainties and external disturbances, where an integral term is used to handle the time-delay input, and a first-order linear filter is used to estimate the derivative of the virtual control input. Both the controller design procedure and the stability criteria are provided. Simulation results demonstrate that the proposed control strategy has satisfactory tracking and disturbance-rejection performance.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133037784","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
Predictive Finite-Time ADRC Based Longitudinal Control for Hypersonic Aircraft with Parametric Uncertainties and Unmodeled Dynamics 具有参数不确定性和未建模动力学的高超声速飞行器的预测有限时间自抗扰控制器纵向控制
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166250
Jinwei Yang
{"title":"Predictive Finite-Time ADRC Based Longitudinal Control for Hypersonic Aircraft with Parametric Uncertainties and Unmodeled Dynamics","authors":"Jinwei Yang","doi":"10.1109/DDCLS58216.2023.10166250","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166250","url":null,"abstract":"It is a significant issue to achieve the fast maneuverability and the strong robustness of hypersonic aircraft. Based on the thoughts of finite-time control and active disturbance rejection control (ADRC), this paper proposes a finite-time ADRC for controlling the longitudinal dynamics of hypersonic aircraft. The proposed design consists of three parts: finite-time feedback, finite-time estimation and estimating predictive modules. To avoid discontinuously changing of control input, the presented finite-time design is in a continuous form. Moreover, to overcome the delay phenomenon of estimation in the conventional ADRC, the predictive values of total disturbance and angular velocity are calculated based on Taylor expansion. The simulations for nonlinear uncertainties validate the effectiveness of the proposed method.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127433214","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
Observer Based Model-Free Adaptive Iterative Learning Constrained Control for Nonlinear Systems 基于观测器的非线性系统自适应迭代学习约束控制
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166932
Fei Hua, Weiming Zhang, Wenzhou Lu, Dezhi Xu
{"title":"Observer Based Model-Free Adaptive Iterative Learning Constrained Control for Nonlinear Systems","authors":"Fei Hua, Weiming Zhang, Wenzhou Lu, Dezhi Xu","doi":"10.1109/DDCLS58216.2023.10166932","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166932","url":null,"abstract":"In this paper, the large class of nonlinear control systems with repeating tasks are addressed by the proposal of a new model-free adaptive iterative learning (MFAILC) constrained control strategy. With the aid of the compact form dynamic linearization (CFDL) technique, a new observer-based pseudo partial derivative (PPD) iterative estimation algorithm is created. Then, an anti-windup compensator would be suggested to modify reference trajectory in to avoid parameter expansion and system instability, with the goal of solving the input constraint problem driven on by actuator saturation. Furthermore, an iterative constrained controller is proposed and the stability of the controller is proved. Finally, it is demonstrated by numerical simulation that the suggested control algorithm has excellent tracking capability and reliability.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115357902","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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