Journal of Control and Decision最新文献

{"title":"Robust control allocation method for uncertain systems based on the algorithms of maximum–minimum and improved fish swarm","authors":"Xingyuan Yang, Xi Tong, Yangwang Fang","doi":"10.1080/23307706.2023.2261939","DOIUrl":"https://doi.org/10.1080/23307706.2023.2261939","url":null,"abstract":"","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135871263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory controllability of neutral stochastic integrodifferential equations with mixed fractional Brownian motion","authors":"Dimplekumar Chalishajar, Ravikumar Kasinathan, Ramkumar Kasinathan, Dhanalakshmi Kasinathan, John A. David","doi":"10.1080/23307706.2023.2271899","DOIUrl":"https://doi.org/10.1080/23307706.2023.2271899","url":null,"abstract":"","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136070356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equilibrium analysis for multi-defender Stackelberg security games under a logit tie-breaking rule","authors":"Ling Chen, Mingchu Li","doi":"10.1080/23307706.2023.2266697","DOIUrl":"https://doi.org/10.1080/23307706.2023.2266697","url":null,"abstract":"AbstractWe introduce a general multi-defender Stackelberg security game where multiple independent defenders jointly protect a same set of targets from being attacked by a common attacker. In the game, Strong Stackelberg Equilibrium is fundamentally problematic, because the notion of ‘breaking ties in defender's favour’ is no longer well defined, as we must specify which defender will receive the favour. To address this issue, we define a new equilibrium concept under a newly defined tie-breaking rule. We characterise Logit Stackelberg Multi-Defender Equilibrium, corresponding to a logit tie-breaking rule, as well as an equivalent Nash Equilibrium among defenders, and exhibit algorithms for computing the equilibrium solutions. We find that Logit Stackelberg Multi-Defender Equilibrium and its' equivalent Nash Equilibrium may not exist, which motivates us to find an approximate equilibrium. We design a revised exclusion algorithm to find the approximate ε-Nash Equilibrium in which no defender gains more than ε by deviating.KEYWORDS: Multi-defender security gametie-breaking rulelogit Stackelberg multi-defender equilibriumNash equilibriumexclusion method AcknowledgmentsThe authors thank the editor and the anonymous referees for their valuable comments and suggestions, which greatly helped improve the content and presentation of this article.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe paper is supported by the National Natural Science Foundation of China [grant numbers 61572095, 61877007] and Department of Science and Technology of Shanxi Province [grant numbers 20210302124303, 202203021222251].Notes on contributorsLing ChenLing Chen received the B.S. degree in statistics from Shandong University, Weihai and the Ph.D. degree in mathematics from Dalian University of Technology. Starting from 2021, she is working as a lecturer at Taiyuan Normal University. Her current research includes security game, optimisation and decision-making.Mingchu LiMingchu Li received the B.S. degree in mathematics from Jiangxi Normal University, in 1983, the M.S. degree in applied science from the University of Science and Technology Beijing, in 1989, and the Ph.D. degree in mathematics from the University of Toronto, in 1997. He was an Associate Professor at the University of Science and Technology Beijing, from 1989 to 1994. He was engaged in the research and development of information security at Long View Solution Inc. and Compute Ware Inc., from 1997 to 2002. Since 2002, he has been a Full Professor with the School of Software, Tianjin University. He has been at the School of Software Technology, Dalian University of Technology, as a Full Professor, a Ph.D. Supervisor, and the Vice Dean. His main research interests include theoretical computer science and cryptography. His other research interests include graph theory, network security, and game theory.","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136134694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust fault-tolerant control of a class of uncertain nonlinear switched systems with actuator saturation","authors":"Yahui Li, Xiaoyin Li, Xinquan Zhang","doi":"10.1080/23307706.2023.2260817","DOIUrl":"https://doi.org/10.1080/23307706.2023.2260817","url":null,"abstract":"AbstractThis paper addresses the robust fault-tolerant control problem for a class of uncertain nonlinear switched systems with actuator saturation. Our aim is to design a switching law and a robust fault-tolerant control law for guaranteeing that the closed-loop system is asymptotically stabilizable, while at the same time the attraction domain estimation is as large as possible. By using the multiple Lyapunov functions method, sufficient conditions for robust fault-tolerant stabilisation are proposed for the closed-loop system. Then, when some scalar parameters are given in advance, the problem of fault-tolerant controller design and attraction domain estimation is transformed into a convex optimisation problem with linear matrix inequality (LMI) constraints. Finally the validity of the proposed design method is verified by a numerical example.Keywords: Switched systemsfault-tolerant controlattraction domainmultiple Lyapunov functionsactuator saturation Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Scientific Research Fund of Education Department of Liaoning Province of China [grant number LJKMZ20220731]. This work was supported by the Natural Science Foundation of Liaoning Province of China [grant number 2020-MS-283].Notes on contributorsYahui LiYahui Li received the B.S. degree from Hebei Normal University Of science & technology, Now she is working towards the Master degree at school of Information and Control Engineering, Liaoning Petrochemical University, Fushun, China. Her research interest focuses on switched systems and fault-tolerant control.Xiaoyin LiXiaoyin Li received the B.Sc. degree in Computer Information Management from Shenyang Normal University in Shenyang, China, in 2007. She completed her M.Sc. degree in Mathematics and Applied Mathematics from Liaoning Technical University in Fuxin, China, in 2011. Her research interests include switched systems, saturated systems and system performance optimisation.Xinquan ZhangXinquan Zhang received the B.Sc. degree in Automation and M.Sc. degree in Control Theory & Engineering from Liaoning Technical University in Fuxin, China, in 2003 and 2007, respectively. He completed his Ph.D. in Control Theory and Control Engineering in 2012 at the College of Information Science & Engineering, of the Northeastern University of Shenyang, China. Since 2017, as an associate professor, he has been with School of Information and Control Engineering, Liaoning Petrochemical University, China. His research interests include switched systems, robust control and systems control under constraints.","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135412463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent demand forecasting in marketing sector using concatenated CNN with ANFIS enhanced by heuristic algorithm","authors":"N. Srikanth Reddy","doi":"10.1080/23307706.2023.2257695","DOIUrl":"https://doi.org/10.1080/23307706.2023.2257695","url":null,"abstract":"AbstractThis task introduces a novel demand forecasting method using concatenated Convolutional Neural Network (CNN) with an Adaptive Network-based Fuzzy Inference System (ANFIS). The data regarding the historical demand and sales data in integration with ‘advertising effectiveness, expenditure, promotions, and marketing events data' are collected initially. Then, the first-order statistical metrics and second-order statistical metrics are determined as the significant features of the data. Finally, the forecasting is performed by the concatenation of modified CNN with ANFIS termed Concatenated Learning Model (CLM), in which the CNN learns the optimal features that are forecasted by the ANFIS layer instead of the fully connected layer. Deer Hunting with Modified Wind Angle Search (DH-MWS) is used to enhance the CNN and ANFIS architecture, ensuring better performance during forecasting. Simulation findings demonstrate that when the proposed solution is applied to public data, the store achieves improved accuracies concerning intelligent demand forecasting in the marketing sector.KEYWORDS: Demand forecastingmarketing sectorconcatenated learning modeldeer hunting with modified wind angle search Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsN. Srikanth ReddyN. Srikanth Reddy. A Commerce graduate with Post-Graduation in Management and Doctorate in Management. More than 15 years of experience in education and research. Areas of interest include Marketing, Systems and Analytics.","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"I&I adaptive fault-tolerant control of a class of nonaffine systems with nonlinearly parameterised faults","authors":"Min Zhang, Xiangbin Liu, Xiaoyu Zhang, Hongye Su","doi":"10.1080/23307706.2023.2260812","DOIUrl":"https://doi.org/10.1080/23307706.2023.2260812","url":null,"abstract":"AbstractThis paper provides a novel fault-tolerant control scheme for a class of nonaffine systems with nonlinearly parameterised (NLP) faults. The nonaffine system is firstly transformed into an augmented one via dynamic feedback control. A fault-tolerant controller with Immersion and Invariance (I&I) adaptation law is designed for the transformed system through dynamic surface control. The controller avoids complexity due to the explosion of terms in backstepping design. The I&I adaptation law is developed to recover the unknown parameters of NLP faults in the system. The proposed scheme can shape the transient performance of the parameter estimation error and tracking error. In the tracking problem, all the signals and tracking error converge exponentially to a small neighbourhood of the origin. In the regulation problem, the system output converges exponentially to zero. A numerical simulation is carried out to verify the effectiveness of the proposed scheme.Keywords: Immersion and invariance manifolddynamic feedback controldynamic surface controlnonaffine systemsnonlinearly parameterisation Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Fundamental Research Funds for the Central Universities [grant number 2022YJS021] and [grant number 2022JBZY001]; the National Natural Science Foundation of China [grant number 62371032].Notes on contributorsMin ZhangMin Zhang received her B.S. degree from Zhengzhou University, China, in 2019. She is currently working toward the Ph.D. degree in control science and engineering with Beijing Jiaotong University, Beijing, China. Her main research interests include adaptive control, nonlinear control and fault-tolerant control.Xiangbin LiuXiangbin Liu received his B.S. degree from Xi'an Institute of Technology, China, in 1995, M.S. degree from University of Science and Technology Beijing, China, in 2002, and Ph.D. degree from Zhejiang University, China, in 2009, respectively. He is currently an Associate Professor with Beijing Jiaotong University (BJU). His research interests include adaptive control, robust control and nonlinear control.Xiaoyu ZhangXiaoyu Zhang (Senior Member, IEEE) was born in 1978. He received the B.S. degree from Yanshan University, in 2000, and the M.S. and Ph.D. degrees from Zhejiang University, in 2003 and 2006, respectively. From 2006 to 2007, he was with the School of Information Science and Engineering, Nanchang University. From 2007 to 2021, he has been taught with the North China Institute of Science and Technology (NCIST). From 2018 to 2019, he was a Visiting Scholar with Columbia University, New York. He is currently a Professor with Beijing University of Civil Engineering and Architecture (BUCEA). His research interests include nonlinear control, intelligent control, switching systems, driving systems, power electronics, and complex systems.Hongye SuHongye Su (Senior Member, IEEE) was bo","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault prediction model in wind turbines using deep learning structure with enhanced optimisation algorithm","authors":"Mahendra Bhatu Gawali, Swapnali Sunil Gawali, Megharani Patil","doi":"10.1080/23307706.2023.2247420","DOIUrl":"https://doi.org/10.1080/23307706.2023.2247420","url":null,"abstract":"AbstractDigital Twin (DT) is used for lifetime monitoring of the drive train and can be a costly option. This proposal adopts the predictive modelling of wind turbines by digital twins by deep learning strategies. Initially, the data is acquired from publicly available wind turbine datasets. Next, the deep features and statistical features are extracted, and the autoencoder is adapted to get the deep features. Then, the Enhanced Marine Predators Algorithm (EMPA) is to select the optimal weighted fused features, where the EMPA would tune the weights used for fusion and the features selection. Finally, the predictive modelling is done via a newly recommended Adaptive Deep Temporal Convolution Network with an Attention Mechanism (ADTCN-AM). It is tuned for precise outcomes with the help of EMPA for forecasting the wind speed and predicting the generated power. The comparative performance analysis of the recently used wind prediction system model shows better efficient results.KEYWORDS: Twin predictive model in wind turbinesfeature extractionenhanced marine predators algorithmadaptive deep temporal convolution network with attention mechanismoptimal weighted fused features Disclosure statementNo potential conflict of interest was reported by the author(s).Practical implicationThe real-time-based twin prediction model in wind turbines gives the computer-oriented solutions for next-generation. It is utilised to generate a digital copy of wind farms interconnected with the physical wind turbines for analysis and prediction process. It helps analyse and understand wind farms easily. It helps to deal with the issue of real-time control of the characteristics of UAV swarm. It includes context-awareness capabilities, which are utilised to identify cybersecurity problems in real time for smart grid deployments.Additional informationNotes on contributorsMahendra Bhatu GawaliMahendra Bhatu Gawali received his BE degree in 2008, M.E. degree in 2013 and Ph.D. degree in 2019 from University of Mumbai, MS, India. Currently he working as Professor in IT department of Sanjivani College of Engineering, Kopargaon, Savitribai Phule Pune University, Pune, MS, India. His area of interests is Digital Twin, Cognitive Intelligence, Artificial Intelligence, Cloud Computing, Optimisation.Swapnali Sunil GawaliSwapnali Sunil Gawali is working as assistant professor in the computer engineering department of Sanjivani College of Engineering, Kopargaon. She has completed her BE and ME from Savitribai Phule Pune University, Pune. Her area of interest is data mining, artificial intelligence.Megharani PatilMegharani Patil is an associate professor in the computer engineering department of Thakur College of Engineering and Technology, Mumbai, and head of the department of artificial intelligence and machine learning. She has received her PhD from the University of Mumbai. Her area of research interest is user experience design and intelligent systems. She has published her research pa","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135385861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"False data injection attacks on networked control systems","authors":"Syed Ahmed Pasha, Rijha Safdar, Syed Taha Ali","doi":"10.1080/23307706.2023.2261938","DOIUrl":"https://doi.org/10.1080/23307706.2023.2261938","url":null,"abstract":"AbstractThe integration of cyber (network) with physical world is a big step in cyber-physical systems. This has revolutionised many industries. But this transformation has made cyber-physical systems vulnerable to attacks. One particular type of attack is the adversarial false data injection which injects false data in either the sensor measurements or the corresponding communication channel. A better understanding of how false data injection (FDI) attacks are constructed is crucial for developing strategies to protect against such attacks. In this paper, we consider two models for networked control systems and present an algorithm for constructing FDI attacks in each case and compare with an existing approach. The conditions for the attack to remain stealthy for systems equipped with a χ2 failure detector and the design of attack vectors that satisfy these conditions are discussed in detail. The algorithms are demonstrated by developing FDI attacks for two real-world examples.Keywords: False data injectionnetworked control systemcyber-physical systemcyber-attackmalicious data Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsSyed Ahmed PashaSyed Ahmed Pasha was born in Rawalpindi, Pakistan. He has a Bachelors degree in Electrical Engineering (2001). His Ph.D. (UNSW, 2009) is in Electrical Engineering. He has held two postdoc positions (UNSW, 2009–2011 & USyd, 2012–2013). He is currently Associate Professor at Air University, Pakistan and Visiting Fellow at UNSW since 2012. His research interests are in control and signal processing.Rijha SafdarRijha Safdar did her B.E. from Air University, Pakistan in 2015. She received an MS in Electrical Engineering in 2019 from National University of Sciences and Technology, Pakistan, where she is pursuing a Ph.D. in Electrical Engineering. She is currently Assistant Manager at Centre of Excellence in Science & Applied Technologies, Pakistan. Her research interests include control and cyber security.Syed Taha AliSyed Taha Ali did his BSc. from GIK Institute of Engineering Science and Technology in Pakistan in 2002, followed by an MS and PhD in Electrical Engineering from the University of New South Wales, Australia in 2006 and 2012. He did his postdoctoral research at the University of New South Wales, Australia, in 2013, and at Newcastle University, UK from 2014 to 2016. He is currently Associate Professor at National University of Sciences and Technology, Pakistan. His research interests include network security, cryptocurrencies, election protocols, and security applications of computer vision.","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134961119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deterministic differential games in infinite horizon involving continuous and impulse controls","authors":"Brahim El Asri, Hafid Lalioui","doi":"10.1080/23307706.2023.2255594","DOIUrl":"https://doi.org/10.1080/23307706.2023.2255594","url":null,"abstract":"We consider a two-player zero-sum deterministic differential game where each player uses both continuous and impulse controls in infinite-time horizon. We assume that the impulses supposed to be of general term and the costs depend on the state of the system. We use the dynamic programming principle and viscosity solutions approach to show existence and uniqueness of a solution for the Hamilton-Jacobi-Bellman-Isaacs (HJBI) partial differential equations (PDEs) of the game. We prove under Isaacs condition that the upper and lower value functions coincide.","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135924790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive fault-tolerant control on complex networks with semi-Markov jump topology under random packet loss","authors":"Yunhan Qi, Lei Su, Rongsheng Xia, Tian Fang, Hao Shen","doi":"10.1080/23307706.2023.2250367","DOIUrl":"https://doi.org/10.1080/23307706.2023.2250367","url":null,"abstract":"In this paper, semi-Markov process and adaptive fault-tolerant law are used to study the synchronization of complex networks in the presence of topology mutations and actuator failures. Firstly, the semi-Markov jump process, which is more practical than the traditional Markov jump process, is used to simulate the topology change of complex networks. Secondly, by designing adaptive fault-tolerant controller, the influence of actuator fault and interference on the system is eliminated. Then, considering the random packet loss caused by network channel congestion and limited bandwidth resources, a control strategy is developed to achieve convergence of the synchronisation error system. Finally, a numerical example and a practical example of Chua's circuit are given to verify the validity of the proposed theory.","PeriodicalId":37267,"journal":{"name":"Journal of Control and Decision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135826207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}