International Journal of Adaptive Control and Signal Processing最新文献_第6页

Event triggering fixed time secondary control of DC microgrid considering FDI attacks 考虑 FDI 攻击的直流微电网事件触发固定时间二级控制

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-23 DOI: 10.1002/acs.3875

Zhongqiang Wu, Shaochen Geng, Zongkui Xie

{"title":"Event triggering fixed time secondary control of DC microgrid considering FDI attacks","authors":"Zhongqiang Wu, Shaochen Geng, Zongkui Xie","doi":"10.1002/acs.3875","DOIUrl":"10.1002/acs.3875","url":null,"abstract":"<div>\u0000 \u0000 <p>Aiming at the problem that distributed secondary control is vulnerable to FDI attacks in DC microgrid, which affects the stability of the system, and the problems of communication redundancy and energy loss in traditional distributed secondary control, an event triggered fixed time distributed secondary control scheme based on high-order differentiator is proposed. The high-order differentiator is used to estimate the FDI attack signal of the system. Then, using the estimated attack signal, a fixed time distributed secondary controller based on event triggering is designed to eliminate the impact of the attack signal, and realize the adjustment of bus voltage and accurate power distribution. The strict stability and the absence of Zeno behavior are proved. The simulation results show that the proposed control strategy can significantly reduce the impact of attacks on the system, and the event triggered fixed time control reduces the energy consumption of the system and the update numbers of the controller, making the system have better dynamic performance.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 10","pages":"3311-3328"},"PeriodicalIF":3.9,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive fuzzy ABLF function fixed-time tracking control method for nonlinear fault-tolerant control systems with event triggering mechanism 具有事件触发机制的非线性容错控制系统的自适应模糊 ABLF 函数固定时间跟踪控制方法

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-22 DOI: 10.1002/acs.3873

Guodong You, Xingyun Li, Jinyuan Wu, Bin Xu, Leijiao Ge, Zhifang Shen, Hailong Zhang

{"title":"Adaptive fuzzy ABLF function fixed-time tracking control method for nonlinear fault-tolerant control systems with event triggering mechanism","authors":"Guodong You, Xingyun Li, Jinyuan Wu, Bin Xu, Leijiao Ge, Zhifang Shen, Hailong Zhang","doi":"10.1002/acs.3873","DOIUrl":"10.1002/acs.3873","url":null,"abstract":"<div>\u0000 \u0000 <p>As the nonlinearities of many real physical controlled systems become stronger and stronger, they are difficult to be described by accurate mathematical models. For a class of nonlinear single-input single-output systems with all-state constraints and actuator faults, an event-triggered adaptive fuzzy ABLF function fixed-time tracking control method is proposed. The asymmetric barrier Lyapunov function (ABLF) combined with backward step technique is used to ensure the boundedness of the closed-loop system output. In order to solve the problem of limited bandwidth resources, this paper adopts the event trigger mechanism and fuzzy control technology to approximate the unknown function to ensure the convergence of the system in a fixed time. After theoretical analysis, it is proved that the tracking error of the system converges in the small neighborhood of the origin, and it still has good tracking performance when the actuator faults. Finally, by comparing the proposed method with the asymmetric barrier Lyapunov function, which verifies the effectiveness of the proposed method.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 9","pages":"3250-3266"},"PeriodicalIF":3.9,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed online optimization for integrated energy systems: A multi-agent system consensus approach 综合能源系统的分布式在线优化：多代理系统共识方法

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-19 DOI: 10.1002/acs.3881

Guofeng Wang, Yongqi Liu, Youbing Zhang, Jun Yan, Shuzong Xie

{"title":"Distributed online optimization for integrated energy systems: A multi-agent system consensus approach","authors":"Guofeng Wang, Yongqi Liu, Youbing Zhang, Jun Yan, Shuzong Xie","doi":"10.1002/acs.3881","DOIUrl":"10.1002/acs.3881","url":null,"abstract":"<div>\u0000 \u0000 <p>The integration of multi-energy within distribution networks has escalated the need for efficient operation and control of integrated energy systems (IES). Addressing the complexities of real-time scheduling and low-carbon optimization, we propose a novel artificial intelligence driven multi-agent system (MAS) approach for modeling the interactions and operations within the multi-agent integrated energy systems (MA-IES) framework. In this framework, distinct components such as electric, gas, and heat networks are conceptualized as autonomous agents, each responsible for managing its domain while interacting with other agents to achieve system-wide efficiency and economical goals. The agents communicate and coordinate through a distributed online optimization framework, utilizing the alternating direction multiplier method (ADMM) to ensure effective consensus despite the inherent nontransparency of information exchange. This MAS based approach allows for dynamic adaptation of strategies based on local data and global objectives, significantly enhancing the responsiveness and adaptability of MA-IES. We further integrate an objective function reliant on a tiered carbon pricing mechanism to assess and minimize the environmental impact of operations. Enhanced by adaptive penalty coefficients within the ADMM, our MA-IES framework demonstrates improved convergence rates and robustness in operational scenarios. Empirical validation through detailed case studies confirms the superior performance of our MAS-based model, demonstrating its potential to realize an efficient and economical low-carbon operation of MA-IES.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 10","pages":"3401-3421"},"PeriodicalIF":3.9,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predefined time formation control for glide multiple aircraft under event-triggered mechanism 事件触发机制下多飞机滑翔的预定时间编队控制

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-18 DOI: 10.1002/acs.3880

Yuehui Ji, Zhaotao Ke, Yu Song, Qiang Gao, Junjie Liu

{"title":"Predefined time formation control for glide multiple aircraft under event-triggered mechanism","authors":"Yuehui Ji, Zhaotao Ke, Yu Song, Qiang Gao, Junjie Liu","doi":"10.1002/acs.3880","DOIUrl":"10.1002/acs.3880","url":null,"abstract":"<div>\u0000 \u0000 <p>This article investigates the event-triggered predefined time gliding formation control for multiple aircraft based on the leader-follower mode. For the banked-to-turn (BTT) aircraft, The main technical challenge is to realize a predefined time control from the aerodynamic control surfaces to the direction of flight speed under an event-triggered mechanism. First, under the leader-follower mode, the desired tracking commands for the leader's trajectory inclination angle and trajectory declination angle are designed, with followers set to track the leader's outputs. Second, for each BTT aircraft, the inner and outer loop control system is constructed, and the virtual angle of attack and flight path angle laws are formulated to decouple the inner-outer structure. For the outer loop system, the predefined time-stabilized of trajectory inclination angle and trajectory declination angle is achieved by introducing the time scale function. Concerning the inner-loop system, a sliding mode surface with predefined time stabilization is constructed, and a predefined time extended state observer (PTESO) is designed to estimate the total disturbances. An event-triggered predefined time control is proposed for the aerodynamic control surfaces to realize the aircraft's flight direction tracking. Finally, the stability of the closed-loop system and the avoidance of the Zeno phenomenon for each aircraft is proved using Lyapunov's theory. The simulation results verify the effectiveness of the proposed formation control in the article.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 10","pages":"3381-3400"},"PeriodicalIF":3.9,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal strategy of data tampering attacks for FIR system identification with average entropy and binary-valued observations 利用平均熵和二值观测数据识别 FIR 系统的最佳数据篡改攻击策略

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-18 DOI: 10.1002/acs.3877

Zhongwei Bai, Yan Liu, Yinghui Wang, Jin Guo

引用次数: 0

Composite-observer-based asynchronous control for hidden Markov nonlinear systems with disturbances 基于复合观测器的有扰动隐马尔可夫非线性系统异步控制

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-15 DOI: 10.1002/acs.3872

Weidi Cheng, Shuping He, Hai Wang, Changyin Sun

引用次数: 0

Decentralized adaptive practical prescribed-time control via command filters 通过指令滤波器实现分散自适应实用规定时间控制

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-11 DOI: 10.1002/acs.3876

Wei Zhang, Tianping Zhang

{"title":"Decentralized adaptive practical prescribed-time control via command filters","authors":"Wei Zhang, Tianping Zhang","doi":"10.1002/acs.3876","DOIUrl":"10.1002/acs.3876","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes a command filter-based decentralized adaptive backstepping practical prescribed-time (PPT) tracking control scheme for a class of non-strict feedback interconnected systems with time varying parameters, unknown control coefficients, unmodeled dynamics, input deadzone and saturation. By the aid of the characteristics of Gaussian functions, the obstacles arising from the non-strict feedback terms are successfully solved. By constructing a novel time-varying scaling function and utilizing nonlinear mapping, the PPT tracking control is developed. The estimations of dynamical uncertainties resulting from unmodeled dynamics are accomplished by employing auxiliary signals, while the unknown continuous terms are characterized by the aid of radial basis function neural networks (RBFNNs). A superposition of two hyperbolic tangent functions is utilized to approximate input nonlinearity. Utilizing the compact set defined in the command filtered backstepping technique, the problem of unknown control direction is solved without using the Nussbaum gain technique. All the signals involved are proved to be semi-global uniform ultimate bounded, and the tracking error can enter the pre-specified convergence region within a pre-specified time. Simulation results are used to demonstrate the effectiveness of the proposed control approach.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 10","pages":"3290-3310"},"PeriodicalIF":3.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141614841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection of breast cancer by deep belief network with improved activation function 利用改进激活函数的深度信念网络检测乳腺癌

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-09 DOI: 10.1002/acs.3861

S. Archana

{"title":"Detection of breast cancer by deep belief network with improved activation function","authors":"S. Archana","doi":"10.1002/acs.3861","DOIUrl":"10.1002/acs.3861","url":null,"abstract":"<div>\u0000 \u0000 <p>Breast cancer is the most prevalent kind of tumor to occur in females and the primary cause of death for women. Early detection is perhaps the most successful strategy to minimize breast cancer mortality. Early diagnosis necessitates a consistent and efficient diagnostics method that allows doctors to differentiate benign from malignant breast cancers without a surgical sample. The goal of this endeavor is to develop a sophisticated breast cancer diagnosis method. The primary goal of the paper is to reduce the death rate among women by promoting early detection of breast cancer. First, pre-processing techniques such as median filtering and contrast limiting adaptive histogram equalization are used to the obtained raw images. By doing this, the machine-learning model's computational complexity is decreased and the image quality is enhanced. K-means clustering is used to segregate the pre-processed image. Additionally, features including the enhanced local vector pattern, grey-level co-occurrence matrix and local vector patterns are produced in the course of the feature extraction stage. Finally, an optimized deep belief network (DBN) is carrying out the classification process. To boosts the classification accuracy, activation function of DBN (tan<i>h</i>, softmax, ReLu) as well as its weight function is optimized by the proposed grey wolf updated whale optimization algorithm The accuracy of the greywolf updated whale optimization algorithm+DBN is above 93% for datasets 1 and 2 when compared to extant models. Finally, calculation of the performance validates the proposed model's performance.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 9","pages":"3074-3101"},"PeriodicalIF":3.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141573757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parameter estimation methods for time-invariant continuous-time systems from dynamical discrete output responses based on the Laplace transforms 基于拉普拉斯变换的动态离散输出响应的时不变连续时间系统参数估计方法

IF 3.9 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-03 DOI: 10.1002/acs.3871

Kader Ali Ibrahim, Feng Ding

引用次数: 0

Intelligent fault diagnosis of rolling bearings in strongly noisy environments using graph convolutional networks 利用图卷积网络对强噪声环境中的滚动轴承进行智能故障诊断

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-03 DOI: 10.1002/acs.3869

Lunpan Wei, Xiuyan Peng, Yunpeng Cao

{"title":"Intelligent fault diagnosis of rolling bearings in strongly noisy environments using graph convolutional networks","authors":"Lunpan Wei, Xiuyan Peng, Yunpeng Cao","doi":"10.1002/acs.3869","DOIUrl":"https://doi.org/10.1002/acs.3869","url":null,"abstract":"SummaryRolling bearings often function under complex and non‐stationary conditions, where significant noise interference complicates fault diagnosis by obscuring fault characteristics. This paper presents an innovative fault diagnosis technique using graph convolutional networks (GCN) to address these challenges. Vibration signals are first transformed into the frequency domain through fast Fourier transform (FFT), creating a detailed graph where nodes and edges encapsulate fault signals. The GCN method then extracts complex node features from this graph, enabling a classifier, comprising a fully connected layer and Softmax function, to accurately identify fault types. Experimental results demonstrate the superior performance of the proposed GCN‐based fault diagnosis method, achieving an accuracy of 99.79%. This significantly surpasses traditional machine learning methods (85.4%), deep learning models (92.3%), and other graph neural network approaches (94.1%). Notably, the method shows exceptional resilience to noise, maintaining high accuracy even with 20% added noise, underscoring its robustness for practical industrial applications. The transformation of vibration signals into the frequency domain using FFT, followed by constructing a detailed graph structure, enables the GCN to effectively capture and represent intricate fault characteristics, thus enhancing accurate fault classification. These findings highlight the method's practical applicability and potential for deployment in advanced industrial settings characterized by high noise levels and complexity.","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"76 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141546693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0