Article
Automation & Control Systems
Yihao Xu, Alexandre Seuret, Kun Liu, Senchun Chai
Summary: The recent literature on event-triggered control has shown the potential of dynamic periodic event-triggered control. The benefit of considering periodic event-triggered control is to avoid the Zeno phenomenon. This paper proposes a generic framework to emulate aperiodic dynamic event-triggered control law and relaxes the constraint on the periodicity of the allowable sampling instants.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2024)
Article
Automation & Control Systems
Longxin Zhang, Jingsheng Chen, Jianguo Chen, Zhicheng Wen, Xusheng Zhou
Summary: This study proposes a lightweight PCB image defect detection network (LDD-Net) that achieves high accuracy by designing a novel lightweight feature extraction network, multi-scale aggregation network, and lightweight decoupling head. Experimental results show that LDD-Net outperforms state-of-the-art models in terms of accuracy, computation, and detection speed, making it suitable for edge systems or resource-constrained embedded devices.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zhihao Xu, Zhiqiang Lv, Benjia Chu, Zhaoyu Sheng, Jianbo Li
Summary: Predicting future urban health status is crucial for identifying urban diseases and planning cities. By applying an improved meta-analysis approach and considering the complexity of cities as systems, this study selects eight urban factors and explores suitable prediction methods for these factors.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yulong Ye, Qiuzhen Lin, Ka-Chun Wong, Jianqiang Li, Zhong Ming, Carlos A. Coello Coello
Summary: This paper proposes a localized decomposition evolutionary algorithm (LDEA) to tackle imbalanced multi-objective optimization problems (MOPs). LDEA assigns a local region for each subproblem using a localized decomposition method and restricts the solution update within the region to maintain diversity. It also speeds up convergence by evolving only the best-associated solution in each subproblem while balancing the population's diversity.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Soung Sub Lee
Summary: This study proposed a satellite constellation method that utilizes machine learning and customized repeating ground track orbits to optimize satellite revisit performance for each target.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yuhang Gai, Bing Wang, Jiwen Zhang, Dan Wu, Ken Chen
Summary: This paper investigates how to reconfigure existing compliance controllers for new assembly objects with different geometric features. By using the proposed Equivalent Theory of Compliance Law (ETCL) and Weighted Dimensional Policy Distillation (WDPD) method, the learning cost can be reduced and better control performance can be achieved.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Kemal Ucak, Gulay Oke Gunel
Summary: This paper introduces a novel adaptive stable backstepping controller based on support vector regression for nonlinear dynamical systems. The controller utilizes SVR to identify the dynamics of the nonlinear system and integrates stable BSC behavior. The experimental results demonstrate successful control performance for both nonlinear systems.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Mahathi Anand, Abolfazl Lavaei, Majid Zamani
Summary: This paper proposes a compositional scheme for constructing control barrier certificates for interconnected discrete-time stochastic systems, which can synthesize switching controllers satisfying w-regular properties and provide probabilistic guarantees for specification satisfaction. The proposed scheme leverages interconnection topology and control sub-barrier certificates of subsystems to compositionally construct control barrier certificates of interconnected systems.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2024)
Article
Automation & Control Systems
Nikolaos Bekiaris-Liberis, Delphine Bresch-Pietri, Nicolas Petit
Summary: We consider a model of a microfluidic process under Zweifac-Fung effect, which gives rise to a second-order nonlinear, non-affine system with control input that affects the plant both without delay and with an input-dependent delay defined implicitly through an integral of the past input values. We construct a predictor-feedback control law that exponentially stabilizes the output to a desired reference point. This is the first time that a predictor-feedback design is constructed that achieves complete input delay compensation for such a type of input delay and despite that control input affects the plant also without delay.
Article
Automation & Control Systems
Lars A. L. Janssen, Bart Besselink, Rob H. B. Fey, Nathan van de Wouw
Summary: This paper introduces a mathematical relationship between the accuracy of reduced-order linear-time invariant subsystem models and the stability and accuracy of the resulting reduced-order interconnected linear time-invariant model. This result can be used to directly translate the accuracy characteristics of the reduced-order subsystem models to the accuracy properties of the interconnected reduced-order model, or to translate accuracy requirements on the interconnected system model to accuracy requirements on subsystem models.
Article
Automation & Control Systems
Demian Garcia-Violini, Yerai Pena-Sanchez, Nicolas Faedo, Fernando Bianchi, John V. Ringwood
Summary: This study presents a model invalidation methodology for wave energy converters (WECs) that can effectively handle dynamic uncertainty and external noise. The results indicate that neglecting dynamic uncertainty can lead to overestimation of performance, highlighting the importance of accurate dynamic description for estimating control performance.
CONTROL ENGINEERING PRACTICE
(2024)
Review
Automation & Control Systems
Vivek Warke, Satish Kumar, Arunkumar Bongale, Pooja Kamat, Ketan Kotecha, Ganeshsree Selvachandran, Ajith Abraham
Summary: This study conducts a systematic literature review on the use of active vibration control (AVC) techniques for improving the useful life of cutting tools. The review highlights the significance of AVC in mitigating the detrimental effects of vibrations on tool performance, focusing particularly on the use of MR fluid in AVC and its characteristics, modeling, and control techniques. The study also briefly discusses data-driven methods for estimating the remaining useful life (RUL) of cutting tools. The findings of this review provide a comprehensive overview of current research in the field and offer valuable insights for researchers, engineers, and practitioners engaged in tool design, maintenance, and optimization, ultimately contributing to the advancement of AVC techniques and promoting sustainable practices in various industrial sectors.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zahra Ramezanpoor, Adel Ghazikhani, Ghasem Sadeghi Bajestani
Summary: Time series analysis is a method used to analyze phenomena with temporal measurements. Visibility graphs are a technique for representing and analyzing time series, particularly when dealing with rotations in the polar plane. This research proposes a visibility graph algorithm that efficiently handles biological time series with rotation in the polar plane. Experimental results demonstrate the effectiveness of the proposed algorithm in both synthetic and real world time series.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Kanishke Gamagedara, Taeyoung Lee, Murray Snyder
Summary: This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle capable of autonomously taking off and landing on a moving vessel in ocean environments. The flight hardware consists of a general-purpose computing module connected to a low-cost inertial measurement unit, real-time kinematics GPS, motor speed controller, and a camera through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading to execute control, estimation, and communication tasks simultaneously. The proposed flight system is verified through autonomous flight experiments on a research vessel in Chesapeake Bay, utilizing real-time kinematics GPS for relative positioning and vision-based autonomous flight for shipboard launch and landing.
CONTROL ENGINEERING PRACTICE
(2024)
Correction
Automation & Control Systems
Zhijun Guo, Gang Chen
Article
Automation & Control Systems
Alexander Aleksandrov
Summary: This paper investigates the absolute stability problem for positive Persidskii systems with delay, proposes a special construction method for diagonal Lyapunov-Krasovskii functionals, and derives a criterion for the existence of such functionals guaranteeing the absolute stability, as well as obtaining sufficient conditions for a family of time-delay Persidskii systems to construct a common diagonal Lyapunov-Krasovskii functional. The efficiency of the developed approaches is demonstrated through four examples.
Article
Automation & Control Systems
Wenkai Xu, Chang Liu, Guangxu Wang, Yue Zhao, Jiaxuan Yu, Akhter Muhammad, Daoliang Li
Summary: This paper proposes a novel approach to monitoring water quality for aquaculture based on deep learning and three-dimensional movement trajectory. The improved YOLOv8 model is used to obtain three-dimensional position information of fish. Experimental results show that the proposed approach achieves high precision and recall in the recovery experiment of acute ammonia nitrogen stress.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yuan Tian, Chunxue Li, Jing Liu
Summary: Competition is a common biological relationship in nature, especially for fish species. This study proposes three novel mathematical models for competition between two fish populations, with control based on linear correlation feedback. The models consider different scenarios and purposes, including avoiding extinction of an inferior population, maximizing economic benefits, and preventing extinction due to unequal competition. The study provides effective control strategies and parameter optimization designs for these scenarios. Numerical simulations are conducted to demonstrate the theoretical results and feasibility of the control strategies. The findings contribute to our understanding of competition dynamics and provide insights for achieving coexistence in two-population systems.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2024)
Article
Automation & Control Systems
Jiahui Zhang, Jinfu Yang, Fuji Fu, Jiaqi Ma
Summary: This paper introduces an efficient and concise wireframe parsing method called SACWP, which utilizes structural asymmetric convolution and feature aggregation modules to capture long-range contextual features and make accurate predictions. The experimental results demonstrate its effectiveness.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yifan Dong, Naiqi Wu, Zhiwu Li
Summary: This paper addresses the state estimation of timed discrete event systems and proposes an online algorithm for computing state estimations generated by timed observations, by introducing time delay and symbolic techniques.
