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2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)最新文献

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A Variable Parameter Model-Free Adaptive Control Algorithm and Its Application in Distillation Tower System 一种变参数无模型自适应控制算法及其在精馏塔系统中的应用
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275240
Yu Feng, Na Dong, Yongzhou Li, Wenjing Lv
{"title":"A Variable Parameter Model-Free Adaptive Control Algorithm and Its Application in Distillation Tower System","authors":"Yu Feng, Na Dong, Yongzhou Li, Wenjing Lv","doi":"10.1109/DDCLS49620.2020.9275240","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275240","url":null,"abstract":"In order to achieve better control performance of chemical process, model free adaptive control (MFAC) scheme is improved by adding two new parameters L1, L2, furthermore to apply in distillation tower system. Compared with basic MFAC, the number of parameters in this novel method is reduced and variable. Firstly, nonlinear system with time-varying desired output is used to carry out numerical simulation for the sake of verifying the effectiveness of this algorithm. After that, the improved MFAC algorithm is applied to the control of the distillation tower system, and the result fully demonstrates the proposed algorithm has strong stability, fast tracking speed. At last, for many systems with time delay in chemical process, such as distillation tower system, a set of validated control method frameworks is proposed in this paper. It is expected to be universally popularized and applied to the control of chemical process.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123872320","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
On the Equivalence between PID-like controller and LADRC for second-order systems 二阶系统类pid控制器与LADRC的等价性
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275160
Xiangyang Li, Zhiqiang Gao, W. Ai, Senping Tian
{"title":"On the Equivalence between PID-like controller and LADRC for second-order systems","authors":"Xiangyang Li, Zhiqiang Gao, W. Ai, Senping Tian","doi":"10.1109/DDCLS49620.2020.9275160","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275160","url":null,"abstract":"In this paper, the equivalence is established between the linear active disturbance rejection control (LADRC) and the two-degree of freedom (2-DOF) proportional-integral-derivative (PID) with lead-lag compensators. This allows advantage of LADRC, particularly its bandwidth-parameterization strategy, to be incorporated into the run-of-mill PID controllers. Specifically, the competing design objectives in disturbance rejection, tracking, and noise sensitivities can now be handled with ease.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121290114","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: 4
Closed-Loop Pitch Attitude Control of Biomimetic Robotic Fish 仿生机器鱼俯仰姿态闭环控制
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275134
Yujie Zhang, Zonggang Li, Yajiang Du
{"title":"Closed-Loop Pitch Attitude Control of Biomimetic Robotic Fish","authors":"Yujie Zhang, Zonggang Li, Yajiang Du","doi":"10.1109/DDCLS49620.2020.9275134","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275134","url":null,"abstract":"This paper considers the pitch control of a robotic fish with three degree-of-freedom(DOF) pectoral fins, wire-driven flexible body and a passive caudal fin. The linear model with undetermined parameters is first suggested to describe the dynamics of the pitch angles, which are the control parameters to adjust the posture of robotic fish. Then, a control network based on Central Pattern Generators(CPGs) is proposed to separately adjust the state of each DOF. Finally, a compound controller is designed to adjust the amplitudes of pectoral Fins such that the desired pitch angle is tracked, in which an adaptive law combined with RBF neural network is proposed to estimate the undetermined parameters. The stability of the proposed algorithm is proved and then the validity is investigated by the simulation results.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128688364","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: 3
Consensus tracking for discrete distributed parameter multi-agent systems via iterative learning control 基于迭代学习控制的离散分布参数多智能体系统一致性跟踪
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275131
Cun Wang, X. Dai, Qingnan Huang, Jingjing Wang, Su Wang
{"title":"Consensus tracking for discrete distributed parameter multi-agent systems via iterative learning control","authors":"Cun Wang, X. Dai, Qingnan Huang, Jingjing Wang, Su Wang","doi":"10.1109/DDCLS49620.2020.9275131","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275131","url":null,"abstract":"In this paper, the consensus tracking problem of discrete distributed parameter multi-agent systems are studied. The communication topology of the system remains unchanged, and only some agents can directly obtain the trajectory information of the virtual leader. An iterative learning control law including the consensus error between any two agents in the system is designed, and the convergence condition of the algorithm is obtained with the help of the contraction mapping principle. In the sense of L2 norm, the consensus tracking error among all agents in the system can converge to zero along the iteration axis. Finally, simulation examples prove the applicability of the algorithm.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128715542","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
A Finite Time Neural Network Model for Solving Time-varying Matrix Inequality Problem 求解时变矩阵不等式问题的有限时间神经网络模型
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275038
Tanglong Hu, Junwen Zhou, Y. Kong
{"title":"A Finite Time Neural Network Model for Solving Time-varying Matrix Inequality Problem","authors":"Tanglong Hu, Junwen Zhou, Y. Kong","doi":"10.1109/DDCLS49620.2020.9275038","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275038","url":null,"abstract":"Time-varying matrix inequalities are frequently encountered in many mathematical calculations and engineering applications. To solve time-varying problems in an effective way, a special recursive Zhang neural network (ZNN) is proposed. However, the convergent time of ZNN tends to be infinity. To accelerate the convergent speed, a recurrent neural network model with finite convergent property (FTNN) is presented and is used to solve the linear time-varying matrix inequality problem. Additionally, convergence and stability of the proposed FTNN model are analyzed. Finally, simulations about the FTNN network model shows that the convergence performance of FTNN model is superior than that of ZNN model.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128796032","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
Using semi-supervised cluster method to correct the mislabeled training samples of ECG signals 利用半监督聚类方法对心电信号训练样本进行错标校正
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275143
Pengfei Wu, Senping Tian
{"title":"Using semi-supervised cluster method to correct the mislabeled training samples of ECG signals","authors":"Pengfei Wu, Senping Tian","doi":"10.1109/DDCLS49620.2020.9275143","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275143","url":null,"abstract":"The classification accuracy of electrocardiogram(ECG) signals will decrease when the labels of some samples in the training set are incorrect. To mitigate this negative impact, the semi-supervised method is introduced to correct the mislabeled samples. The proposed method is based on the basic principle that the characteristics of samples of the same category are more similar than those of samples of different categories, so in the feature space,the number of samples of the same category around a sample is more than that of different categories. Cross validation is used to divide the training set into sub training set and validation set, and the samples in the validation set are regarded as unlabeled, k nearest neighbour(KNN) classifier label the samples in the validation set according to the samples in the sub training set. Because there are mislabeled samples in the sub training set, it is difficult for KNN classifier to label all samples in the validation set correctly at one time. So we need to use the above method iteratively. Thus, the mislabeled samples in the training set is basically corrected. Experients on the ECG signal corrected from the MIT-BIH arrhythmia database show the eectiveness of the proposed method.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129175543","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
Long-term RUL Prediction of Bearings with Signal Amplitude Regulation and Accumulative Feature 具有信号幅度调节和累积特征的轴承RUL长期预测
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275213
Xiaoyu Yang, Yong Zhang, Weidong Yang, Yanwei Wang, Ying Zheng
{"title":"Long-term RUL Prediction of Bearings with Signal Amplitude Regulation and Accumulative Feature","authors":"Xiaoyu Yang, Yong Zhang, Weidong Yang, Yanwei Wang, Ying Zheng","doi":"10.1109/DDCLS49620.2020.9275213","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275213","url":null,"abstract":"Remaining Useful Life (RUL) prediction is essential for the running bearings. An accurate RUL estimation can help the maintenance decision reliable. The accuracy of RUL prediction is greatly influenced by the health index feature. Traditional health index feature suffers from the long constant process and the vertical change degradation. In this paper, a regulated amplitude signal and an accumulative feature is proposed. The regulated signal reduces the vertical change degradation, which makes the prediction easily. And the accumulative feature changes the long constant process to an increase process, which makes the prediction possible at the early life time. The Support Vector Regression (SVR) model is adopt for the direct RUL prediction. In order to verify the effective of our method, the PRONOSTIA platform is used. The result shows that our method behavior better than the traditional feature method.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115637868","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 SMC-based Trajectory Tracking Control of Underactuated Overhead Cranes 欠驱动桥式起重机自适应轨迹跟踪控制
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275076
Shengzeng Zhang, Xiongxiong He, H. Zhu, Yuanjing Feng, Qiang Chen, Zhengyang Zhu, Xiaocong Li
{"title":"Adaptive SMC-based Trajectory Tracking Control of Underactuated Overhead Cranes","authors":"Shengzeng Zhang, Xiongxiong He, H. Zhu, Yuanjing Feng, Qiang Chen, Zhengyang Zhu, Xiaocong Li","doi":"10.1109/DDCLS49620.2020.9275076","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275076","url":null,"abstract":"Overhead cranes, which are typically underactuated, are studied systematically nowadays. While, the model widely used in research is ideal. Thus, the corresponding controllers may react badly under external disturbances, unmodeled dynamics and input constraints. To tackle this issue, this paper develops an adaptive version of anti-sway trajectory tracking controller for overhead cranes. First, as to constrained input, we perform a mapping action from the system input to the hyperbolic tangent function. Then adaptation mechanisms are proposed to adjust the modified inputs and the system uncertainty. Such a controller achieves precise positioning and swing suppression despite input saturation, system uncertainty and external disturbances. The crane system proves to be dissipative with the proposed controller. The experiments accomplished on a laboratory-size bridge crane reveal that the proposed controller asymptotically stabilizes all system states.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115744147","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
RGBD Object Recognition and Flat Area Analysis Method for Manipulator Grasping 机械手抓取的RGBD目标识别及平面面积分析方法
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275208
Kaijun Wang, Shan Liu
{"title":"RGBD Object Recognition and Flat Area Analysis Method for Manipulator Grasping","authors":"Kaijun Wang, Shan Liu","doi":"10.1109/DDCLS49620.2020.9275208","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275208","url":null,"abstract":"Grasping guided by visual recognition and positioning is a practical requirement of discrete automation. This paper proposes a general method of using RGBD image recognition, which can recognize object with only one RGB template photograph of the target object, calculate 3D coordinates and pose, and guide the 6 DOF manipulator to grasp object. SIFT(Scale Invariant Feature Transform) is used to extract feature points of template image and real-time scene image and complete matching. Matched feature points are used as seed points to segment target objects in depth image. This method is fast and requires less prior knowledge. In order to optimize the grasping, this paper uses the Shape Index method to locate the flat area on the object which is most suitable for the suction cup. This method can make the grasping system automatically adapt to various objects and overcome the problems of overlapping and partial occlusion.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114677670","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
Safety Risk Assessment of Ship-Based Test System Based on Fuzzy Analytic Hierarchy Process 基于模糊层次分析法的舰载试验系统安全风险评估
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2020-11-20 DOI: 10.1109/DDCLS49620.2020.9275216
Jing Wang, Wei Zheng, Huihui Zhang, Tianyong Deng
{"title":"Safety Risk Assessment of Ship-Based Test System Based on Fuzzy Analytic Hierarchy Process","authors":"Jing Wang, Wei Zheng, Huihui Zhang, Tianyong Deng","doi":"10.1109/DDCLS49620.2020.9275216","DOIUrl":"https://doi.org/10.1109/DDCLS49620.2020.9275216","url":null,"abstract":"In order to evaluate the safety risks and improve the safety and success rate in the ship test system, a safety evaluation method for the ship-based test system based on the fuzzy analytic hierarchy process was proposed. Determining the safety risk assessment index system of ship-based test system is the first step according to the principle of safety system. Then the weight of each risk assessment index is determined through fuzzy analytic hierarchy process. Finally, a comprehensive assessment is performed to determine the risk level combined with the expert scoring method and the weight of risk assessment indicators through an example. The evaluation results show that the evaluation system realizes the quantification of the risk assessment and could provide theoretical guidance and technical reference for the risk analysis and safety management in the ship-based test system.","PeriodicalId":420469,"journal":{"name":"2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126810242","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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