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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Yang, Rongni Zheng, Wei Xing School of Control Science and Engineering Shandong University Jinan Shandong250061 China School of Computing Engineering and Mathematics Western Sydney University SydneyNSW2751 Australia

ISBN: (纸本)9781538666173

In this paper, the observer-based predictive control problem for networked control systems (NCSs) subject to the time-delay is investigated based on the event-triggered strategy. Initially, the output-based event-triggered mechanism is introduced in order to reduce the transmission times effectively in the capacity-limited communication network. Then, the system states are reconstructed from the output measurements by utilizing a popular Luenberger observer. Next, the model-based networked predictive control (NPC) scheme is developed to actively compensate for the communication delay. Moreover, based on analysis of the augmented system, sufficient conditions that guarantee the asymptotic stability of the system are obtained. Finally, a simulation example is given to demonstrate the effectiveness in the reduction of network utilization and compensation for communication delay of the proposed controller design method in NCSs. © 2018 IEEE.

关键词： Networked control systems

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Chinese Image Description Evaluation Method Based on Target Domain Semantic Constraints 3

Chinese Image Description Evaluation Method Based on Target ...

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3rd International Conference on Image Processing and Intelligent control, IPIC 2023

作者： Wang, Zhenhao Sun, Wenyi Wang, Zhengsong Yang, Le School of Computing and Communication Engineering Northeastern University at Qinhuangdao Haigang Hebei Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Haigang Hebei Qinhuangdao China

ISBN: (纸本)9781510668140

To address the problems of insufficient accuracy and difficulty of application in the current Chinese image description field, this paper proposes an evaluation method based on semantic constraints in the target domain. Unlike previous research, this method acts on the output stage of the model, and based on the extraction of key semantics in the target application domain, it is constrained by the macroscopic semantic space of that domain or by introducing external semantic information from other visual tasks. The experiments show that the proposed method effectively improves the semantic coherence between the model output description sentences and the input images in the target domain, and is helpful for the practical application of image description in specific domains. © 2023 SPIE.

关键词： Semantics

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Symptom selection for multi-label data of inquiry diagnosis in traditional Chinese medicine

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Science China(Information Sciences) 2013年第5期56卷 238-250页

作者： SHAO Huan LI GuoZheng LIU GuoPing WANG YiQin School of Computer Engineering and Science Shanghai University Department of Control Science and Engineering Key Laboratory of Ministry of Education for Service Computing and Embedded SystemsTongji University Laboratory of Information Access and Synthesis of TCM Four Diagnosis Shanghai University of Traditional Chinese Medicine

In traditional Chinese medicine(TCM) diagnosis,a patient may be associated with more than one syndrome tags,and its computer-aided diagnosis is a typical application in the domain of multi-label learning of high-dimensional *** is common that a great deal of symptoms can occur in traditional Chinese medical diagnosis,which affects the modeling of diagnostic *** selection entails choosing the smallest feature subset of relevant symptoms,and maximizing the generalization performance of the *** present there are rare researches on feature selection on multi-label data.A hybrid optimization technique is introduced to symptom selection for multi-label data in TCM diagnosis in this paper,and modeling is made by means of four multi-label learning algorithms like k nearest neighbors,*** compare the performance of the algorithm with the current popular dimension reduction algorithms like MEFS(embedded feature selection for multi-Label learning),MDDM(multi-label dimensionality reduction via dependence maximization) on the UCI Yeast gene functional data set and an inquiry diagnosis dataset of coronary heart disease(CHD).Experimental results show that the algorithm we present has significantly improved the *** particular,the improvement on the average precision for the classifier is up to 10.62% and 14.54%.Syndrome inquiry modeling of CHD in TCM is realized in this paper,providing effective reference for the diagnosis of CHD and analysis of other multi-label data.

关键词： multi-label learning feature selection high-dimensionality inquiry of traditional Chinese medicine coronary heart disease

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Distributed Adaptive Fault-Tolerant Output Regulation of Heterogeneous Multi-Agent Systems With Coupling Uncertainties and Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1098-1106页

作者： Chao Deng Weinan Gao Weiwei Che the School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore the Department of Electrical and Computer Engineering Allen E.Paulson College of Engineering and ComputingGeorgia Southern UniversityStatesboroGA 30460 USA the State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027 the Institute of Complexity Science Qingdao UniversityQingdao 266071China

In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystems under the influence of actuator faults. First, distributed finite-time observers are proposed for all subsystems to observe the state of the exosystem. Then, a novel fault-tolerant controller is designed to compensate for the influence of matched system uncertainties and actuator faults. By using the linear matrix inequality technique, a sufficient condition is provided to guarantee the solvability of the considered problem in the presence of mismatched coupling uncertainties. Moreover, it is shown that the system in closed-loop with the developed controller can achieve output regulation by using the Lyapunov stability theory and cyclic-small-gain ***, a numerical example is given to illustrate the effectiveness of the obtained result.

关键词： Adaptive control cyclic-small-gain fault-tolerant control multi-agent systems(MASs)

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An improvement of SAX representation for time series by using wavelet packet decomposition and FastDTW 23

An improvement of SAX representation for time series by usin...

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6th International Conference on Big Data Technologies, ICBDT 2023

作者： Guo, Yonghua Zhu, Kai Cheng, Xu School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Computing Xi'an Shiyou University Xi'an710065 China

ISBN: (纸本)9798400707667

Aiming at the shortcomings of conventional SAX that using the mean value as the eigenvalue may lead to misclassification, this paper comprehensively considers the numerical distribution difference and morphological fluctuation characteristics of time series data. Firstly, wavelet packet decomposition (WPD) can decompose various types of non-smooth random signals into wavelet components at different scales. Firstly, the WPD is used to extract the features of the time series, and then the Fast Dynamic Time Warping (FastDTW) is used to take advantage of the metrics, and the FastDTW metrics are applied to the features to define the global trend indicators. Then, the SAX distance is combined with the trend distance, and an improved distance measure is proposed. Finally, the experimental results on different time series datasets show that the proposed method has the highest classification accuracy in 11 of the 20 datasets, which proves that the representation method proposed in the paper is significantly better than the original SAX representation and the improved SAX representation. © 2023 ACM.

关键词： Time series

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Towards Long Lifetime Battery:AI-Based Manufacturing and Management

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1139-1165页

作者： Kailong Liu Zhongbao Wei Chenghui Zhang Yunlong Shang Remus Teodorescu Qing-Long Han Warwick Manufacturing Group University of WarwickCoventry CV47ALUnited Kingdom National Engineering Laboratory for Electric Vehicles School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China School of Control Science and Engineering Shandong UniversityJinan 250061China Department of Energy Technology Aalborg UniversityAalborg 9220Denmark School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia IEEE

Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification,smart grid,but also strengthen the battery supply *** battery inevitably ages with time,losing its capacity to store charge and deliver it *** directly affects battery safety and efficiency,making related health management *** advancements in automation science and engineering raised interest in AI-based solutions to prolong battery lifetime from both manufacturing and management *** paper aims at presenting a critical review of the state-of-the-art AI-based manufacturing and management strategies towards long lifetime ***,AI-based battery manufacturing and smart battery to benefit battery health are *** the most adopted AI solutions for battery life diagnostic including state-of-health estimation and ageing prediction are reviewed with a discussion of their advantages and *** through designing suitable AI solutions to enhance battery longevity are also ***,the main challenges involved and potential strategies in this field are *** work will inform insights into the feasible,advanced AI for the health-conscious manufacturing,control and optimization of battery on different technology readiness levels.

关键词： Artificial intelligence battery health management battery life diagnostic battery manufacturing smart battery

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Stability of connected and automated vehicles platoon considering communications failures

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Chinese Physics B 2023年第7期32卷 598-609页

作者：刘润坤于海洋任毅龙崔志勇 School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety ControlBeihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100191China

As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical *** can communicate with each other and exchange ***,communication failures can change the platoon system *** characterize this change,a dynamic topology-based car-following model and its generalized form are proposed in this ***,a stability analysis method is ***,taking the dynamic cooperative intelligent driver model(DC-IDM)for example,a series of numerical simulations is conducted to analyze the platoon stability in different communication topology *** results show that the communication failures reduce the stability,but information from vehicles that are farther ahead and the use of a larger desired time headway can improve ***,the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.

关键词： connected and automated vehicle car-following model communication failures string stability

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Variable selection in identification of a high dimensional nonlinear non-parametric system

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control Theory and Technology 2015年第1期13卷 1-16页

作者： Er-Wei BAI Wenxiao ZHAO Weixing ZHENG Department of Electrical and Computer Engineering University of Iowa School of Electronics Electrical Engineering and Computer Science Queen's UniversityBelfast U.K. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science National Center for Mathematics and Interdisciplinary Sciences Chinese Academy of Sciences School of Computing Engineering and Mathematics University of Western Sydney

The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections to various topics and research areas are briefly discussed, including order determination, pattern recognition, data mining, machine learning, statistical regression and manifold embedding. Finally, some results of variable selection in system identification in the recent literature are presented.

关键词： System identification variable selection nonlinear non-parametric system curse of dimensionality

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Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1458-1475页

作者： Jing Liang Hongyu Lin Caitong Yue Ponnuthurai Nagaratnam Suganthan Yaonan Wang School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001 School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China KINDI Center for Computing Research Qatar UniversityDohaQatarand also with the Nanyang Technology UniversitySingapore College of Electrical and Information Engineering and also with the National Engineering Research Center for Robot Visual Perception and Control TechnologyHunan UniversityChangsha 410082China IEEE

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective *** paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision *** to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal *** proposed algorithm adopts a dual-population framework and an improved environmental selection *** utilizes a convergence archive to help the first population improve the quality of *** improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first *** combination of these two strategies helps to effectively balance and enhance conver-gence and diversity *** addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is *** proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

关键词： Benchmark functions diversity measure evolution-ary algorithms multimodal multiobjective optimization.

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A spintronic memristive circuit on the optimized RBF-MLP neural network

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Chinese Physics B 2022年第11期31卷 272-283页

作者： Yuan Ge Jie Li Wenwu Jiang Lidan Wang Shukai Duan School of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set ***,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as *** view of this,a novel radial basis neural network(RBF-MLP)is proposed in this *** connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating ***,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number *** addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin *** is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified National Institute of Standards and Technology(MNIST)dataset classification *** experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

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