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2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)最新文献

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Data-Driven Fault Symptoms Generation and Augmentation for Satellite Attitude Control System 卫星姿态控制系统数据驱动故障症状生成与增强
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455626
Youdao Ma, Wenhan Zhang, Xinyang Liu, Zhenhua Wang, Yi Shen
{"title":"Data-Driven Fault Symptoms Generation and Augmentation for Satellite Attitude Control System","authors":"Youdao Ma, Wenhan Zhang, Xinyang Liu, Zhenhua Wang, Yi Shen","doi":"10.1109/DDCLS52934.2021.9455626","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455626","url":null,"abstract":"This paper studies the data-driven fault symptoms generation and augmentation for satellite attitude control system via an approximate model technique and a generative adversarial network. An approximate model is determined to fit the input and output data of satellite attitude control system. Based on the designed model, a small number of addictive fault symptoms and multiplicative fault symptoms are generated. To obtain abundant symptom data, the generative adversarial network is introduced to augment the fault symptoms. Finally, numerical simulation results are presented to demonstrate the effectiveness of the proposed method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133875714","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
Memory-Based PI-Type Sampled-Data Consensus Control for Nonlinear Multiagent Systems with Time-Varying Delays 时变时滞非线性多智能体系统的基于记忆的pi型采样数据一致性控制
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455479
Jin Yang, Qishui Zhong, Kaibo Shi, S. Zhong, Shengzhi Han
{"title":"Memory-Based PI-Type Sampled-Data Consensus Control for Nonlinear Multiagent Systems with Time-Varying Delays","authors":"Jin Yang, Qishui Zhong, Kaibo Shi, S. Zhong, Shengzhi Han","doi":"10.1109/DDCLS52934.2021.9455479","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455479","url":null,"abstract":"In this paper, the sampled-data consensus problem of nonlinear multiagent systems (MASs) with time-varying delays is investigated. Compared with the widely used sampled-data controller, a proportional integral type (PI-type) protocol utilizing the information of neighbors considering the effects of memory delay is adopted. Then, by adequately considering characteristic about the time-varying delays, an improved time-varying quadratic type of Lyapunov-Krasovskii functional (LKF) is developed. Besides, augmented state vectors and two-sided looped-functional approach are adopting to constructed the LKF, some relaxed matrices in the LKF are not necessarily positive definite. Furthermore, some sufficient criteria are derived to ensure the consistency of the MASs. By solving a series of linear matrix inequalities, the desired memory PI-type sampled-data control gain matrices are obtained. Finally, the numerical examples are presented to illustrate the theoretical results.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124674380","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
Trajectory Tracking Control of High-Altitude Wind Power Parafoil 高空风力伞的轨迹跟踪控制
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455649
Xinyu Long, Mingwei Sun, Minnan Piao, Shengfei Liu, Zengqiang Chen
{"title":"Trajectory Tracking Control of High-Altitude Wind Power Parafoil","authors":"Xinyu Long, Mingwei Sun, Minnan Piao, Shengfei Liu, Zengqiang Chen","doi":"10.1109/DDCLS52934.2021.9455649","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455649","url":null,"abstract":"In order to attenuate the influence of the uncertainties of high altitude parafoil and environment on trajectory tracking control, active disturbance rejection control (ADRC) is used to regulate the trajectory of the high-altitude wind power parafoil. Linear extended state observer (LESO) is designed to estimate and compensate for nonlinear disturbances of the system. The simulation results show that this method has good control precision and fast-tracking velocity.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123010773","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
Robust Adaptive Trajectory tracking Control of a Class of Disturbed Quadrotor Aircrafts 一类受扰四旋翼飞行器的鲁棒自适应轨迹跟踪控制
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455499
Ya-Jun Wu, Hao Tang, Xiao‐Zheng Jin
{"title":"Robust Adaptive Trajectory tracking Control of a Class of Disturbed Quadrotor Aircrafts","authors":"Ya-Jun Wu, Hao Tang, Xiao‐Zheng Jin","doi":"10.1109/DDCLS52934.2021.9455499","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455499","url":null,"abstract":"This paper explores an approach tracking the trajectory of a class of quadrotor aircrafts based on robust adaptive control against bounded disturbances by compensating for the perturbations. According to the Lyapunov stability theorem, the attitude tracking controller is achieved by using the backstepping technique. A simulation example is illustrated to verify the effectiveness of the designed position trajectory tracking controller and robust adaptive attitude trajectory tracking controller.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"20 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113964147","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 controller design for state estimation of Boolean control networks 布尔控制网络状态估计最优控制器设计
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455643
Yantao Chen, Junqi Yang, Lizhi Cui, Junjie Zhu
{"title":"Optimal controller design for state estimation of Boolean control networks","authors":"Yantao Chen, Junqi Yang, Lizhi Cui, Junjie Zhu","doi":"10.1109/DDCLS52934.2021.9455643","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455643","url":null,"abstract":"In this paper, a kind of optimal controller is proposed to estimate the state of Boolean control networks (BCNs). Different from the standard observer, the optimal state estimation is completed by designing the control input instead of directly using it, where the maximum-minimum method is employed such that the state of BCNs can be uniquely estimated in possible short time steps. A set observer is first proposed to estimate the state of BCNs at any time steps. Based on the set observer, an initial output-dependent reconstructible state tree is developed, where an algorithm is provided to generate the nodes of such tree and can be implemented offline. The optimal control sequence for uniquely determining the state of BCNs is derived from the reconstructible state tree by a breadth-first search algorithm, where the output of BCNs is dynamically employed. An example is given to illustrate the applicability and usefulness of the developed methods.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"47 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122846349","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
MKE Scheme for the Control of Dynamic Constrained Redundant Robots Based on Discrete-time Neural Network 基于离散时间神经网络的动态约束冗余机器人MKE控制方案
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455469
Baiyan Liu, Dan Su, Mei Liu, Yang Shi, Shuai Li
{"title":"MKE Scheme for the Control of Dynamic Constrained Redundant Robots Based on Discrete-time Neural Network","authors":"Baiyan Liu, Dan Su, Mei Liu, Yang Shi, Shuai Li","doi":"10.1109/DDCLS52934.2021.9455469","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455469","url":null,"abstract":"It is necessary to make physical constraints on the joints for the redundant robot motion control in order to avoid damage. In this paper, a discrete-time neural network model with minimum kinetic energy as the performance index is proposed, which has predominant convergence performance. Then, a solution in robot motion control is studied and further transformed into a dynamic quadratic programming (QP) with equality and inequality constraints. In addition, for solving the formulated QP problem, a continuous-time neural network model is designed by introducing the Lagrange multiplier method, and a discrete-time neural network model is obtained by the Euler forward difference formula. Moreover, the simulations on robot motion control are carried out, and the simulative results further substantiate the superiority, thus extending a solution for motion control of redundant robots with double-bound constraints.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124277142","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
Modified ADRC Design for Rigid-flexible Coupling Rotary Stage with Filters 带滤波器的刚柔耦合转台的改进自抗扰设计
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455364
Yutai Wei, Zhijun Yang, Youdun Bai
{"title":"Modified ADRC Design for Rigid-flexible Coupling Rotary Stage with Filters","authors":"Yutai Wei, Zhijun Yang, Youdun Bai","doi":"10.1109/DDCLS52934.2021.9455364","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455364","url":null,"abstract":"High-precision rotary stages are applied in many fields, but the bearing friction has a negative impact on tracking performance. Rigid-flexible coupling rotary stage, a novel structure for rotary stage, can convert the friction disturbance into elastic force with flexure hinges. In order to avoid the effect of elastic force, active disturbance rejection control (ADRC) is adopted in this paper for its excellent disturbance rejection ability and independence of accurate modelling. In view of the resonance and high-frequency noise of the system, notch and lead filters are combined with ADRC, which is called modified ADRC. The experimental results show that the modified ADRC has a good effect on eliminating elastic force disturbance, and also has the ability to suppress resonance and high-frequency noise.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125411762","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 exponentially asymptotic tracking control for a one-link manipulator 单连杆机械臂的自适应指数渐近跟踪控制
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455678
Yanjun Liang, Yuanxin Li
{"title":"Adaptive exponentially asymptotic tracking control for a one-link manipulator","authors":"Yanjun Liang, Yuanxin Li","doi":"10.1109/DDCLS52934.2021.9455678","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455678","url":null,"abstract":"This article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130281542","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
The Batch Process Fault Monitoring Using Adversarial Auto-encoder and K-Nearest Neighbor Rule 基于对抗自编码器和k近邻规则的批处理故障监控
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455504
Zeyu Li, Peng Chang, Kai Wang, Pu Wang
{"title":"The Batch Process Fault Monitoring Using Adversarial Auto-encoder and K-Nearest Neighbor Rule","authors":"Zeyu Li, Peng Chang, Kai Wang, Pu Wang","doi":"10.1109/DDCLS52934.2021.9455504","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455504","url":null,"abstract":"In the industrial batch process monitoring domain, the conventional multivariate monitoring methods may not always function well in monitoring faults that have both Non-Linear and Non-Gaussian properties. To enhance the monitoring capability, the adversarial auto-encoder (AAE) was introduced to increase the sensitivity to Non-Gaussian anomalies by projecting non-Gaussian information into a given Gaussian distribution feature space. At the same time, low-dimensional feature space can avoid the problem of “Concentration of measure” and improve the ability to distinguish minor small abnormalities. Therefore, A novel statistic index was constructed in the feature space based on the k-nearest neighbor rule (KNN) to improve the ability of minor fault monitoring. The proposed model is compared with the traditional multivariate statistical process monitoring methods in numerical examples and penicillin fermentation platform, which proves that it has better monitoring ability for minor magnitude and non-Gaussian faults.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129239389","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
Research and Application of a Novel RPCA-SVME based Multiple Faults Recognition 基于RPCA-SVME的多故障识别方法研究与应用
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2021-05-14 DOI: 10.1109/DDCLS52934.2021.9455584
Yuan Xu, Kaiduo Cong, Yang Zhang, Qunxiong Zhu, Yanlin He
{"title":"Research and Application of a Novel RPCA-SVME based Multiple Faults Recognition","authors":"Yuan Xu, Kaiduo Cong, Yang Zhang, Qunxiong Zhu, Yanlin He","doi":"10.1109/DDCLS52934.2021.9455584","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455584","url":null,"abstract":"In the modern industrial process, the likelihood of the occurrence of multiple faults is higher than that of a single fault Comparing with single faults, the multi-faults problem has higher coupling and complexity, thus it is quite important to establish an effective multi-faults recognition model to ensure process safety. In this paper, a multi-fault recognition model based on reconstructed principal component analysis (RPCA) algorithm and support vector machine ensemble (SVME) classifier is proposed to satisfy the needs. First, obtain the principal component information from the original high-dimensional data space. Second, to solve the loss of local feature information, reconstruct the local structural error of the feature space through the inverse mapping matrix, and then align the error to obtain the reconstructed coordinates. Third, based on the One vs. One (OvO) ensemble strategy, an SVME classifier is constructed for multiple faults recognition. Finally, to verify the performance of the proposed RPCA-SVME model, the simulation experiments are made on a Circle dataset and the Tennessee Eastman process (TEP). The comparison results show that the proposed method can guarantee higher diagnostic accuracy and macro F1 score.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130959258","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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