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Automation & Control Systems
Yanan Qi, Xianfu Zhang, Yanjie Chang, Rui Mu
Summary: This paper proposes a switching event-triggered approach to address the global output-feedback stabilization problem for a class of uncertain nonlinear systems. By using an event-triggered mechanism and a logic-based switching mechanism, the proposed approach determines the timing for sampling and switching control parameters, and develops an observer-based control scheme. With the ability to adaptively adjust the control parameter, this scheme has a stronger capability to handle large uncertainties, inherent nonlinearities, and sampling errors.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2024)
Article
Automation & Control Systems
Yan Zhu, Zhendong Sun
Summary: In this work, we address the minimum realization problem for controllability and observability of both continuous-time and discrete-time switched linear systems, and provide results for the tight upper bound.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2024)
Article
Automation & Control Systems
Xueying Ding, Jianquan Lu, Xiangyong Chen
Summary: This paper investigates the stability of impulsive logical dynamic systems (ILDNs) from the perspectives of impulsive disturbance and impulsive control. The existing results on ILDN stability only consider a given impulsive instant sequence (IIS), which is restrictive. The paper proposes necessary and sufficient conditions for ILDN stability under any IIS by constructing a merged ILDN. However, these conditions are too strict as it is uncommon for a stable LDN to remain stable under any IIS. The paper introduces the concepts of impulsive disturbances and impulsive control, and presents sufficient conditions for LDN stability under time-triggered IISs with average impulsive interval. These results are also applied to set stability of ILDNs.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2024)
Article
Automation & Control Systems
Lucas C. Borin, Guilherme Hollweg, Caio R. D. Osorio, Fernanda M. Carnielutti, Ricardo C. L. F. Oliveira, Vinicius F. Montagner
Summary: This work presents a new automated test-driven design procedure for robust and optimized current controllers applied to LCL-filtered grid-tied inverters. The design of control gains is guided by high-fidelity simulations and particle swarm optimization algorithm, considering various normal and abnormal operating conditions. The proposed design ensures superior performance compared with other current control designs.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Jian Wang, Xiuying Zhan, Yuping Yan, Guosheng Zhao
Summary: This paper proposes a method of user recruitment and adaptation degree improvement via community collaboration to solve the task allocation problem in sparse mobile crowdsensing. By matching social relationships and perception task characteristics, the entire perceptual map can be accurately inferred.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Ran Jiao, Wenjie Liu, Ramy Rashad, Jianfeng Li, Mingjie Dong, Stefano Stramigioli
Summary: A novel end-effector bilateral rehabilitation robotic system (EBReRS) is developed for upper limb rehabilitation of patients with hemiplegia, providing simulations of multiple bimanual coordinated training modes, showing potential for application in home rehabilitation.
Article
Automation & Control Systems
Wei He, Xiang Wang, Mohammad Masoud Namazi, Wangping Zhou, Josep M. Guerrero
Summary: The main objective of this paper is to develop a reduced-order adaptive state observer for a large class of DC-DC converters with constant power load, in order to estimate their unavailable states and unknown parameter and achieve an output feedback control scheme. The observer is designed using a generalized parameter estimation based observer technique and dynamic regressor extension and mixing method. The comparison study shows that the observer has the advantage of verifying the observability of the systems for exponential convergence without any extra excitation condition.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Cheng Zhao
Summary: The PID controller is widely used in feedback control, but lacks a satisfactory theory to explain its widespread application. Recent research has shown that the classical PID controller can achieve global stability in a class of uncertain nonlinear systems, but the system nonlinear function needs to have a linear growth rate with respect to the state variables. This paper considers a more general case where the system nonlinear function may have super-linear growth rates and demonstrates that the classical PID control can still stabilize such systems in a semi-global sense.
Article
Automation & Control Systems
Xiangyu Wang, Yujing Xu, Yue Cao, Shihua Li
Summary: This paper proposes a hierarchical design framework for distributed control of multi-agent systems. It decouples cooperation and individual regulations, and divides the control design into two layers: reference signal generator design and tracking controller design. The framework provides better design flexibility and scalability, and is a natural choice for addressing complex factors in multi-agent systems.
Article
Automation & Control Systems
Hossam Seddik Abbas
Summary: This paper investigates the use of linear-parameter varying (LPV) embedding of nonlinear dynamics for model predictive control (MPC). The proposed LPVMPC incorporates information of the future evolution of the scheduling parameter with uncertainty bounds, and constructs anticipated scheduling tubes for robustification. Numerical examples demonstrate the effectiveness of the LPVMPC algorithm compared to nonlinear MPC and other standard approaches.
Article
Automation & Control Systems
Ammar Chouchane, Mohcene Bessaoudi, Hamza Kheddar, Abdelmalik Ouamane, Tiago Vieira, Mahmoud Hassaballah
Summary: Video surveillance image analysis and processing is an important field in computer vision, and Person Re-Identification (PRe-ID) is a challenging task within this field. This article proposes a method called High-Dimensional Feature Fusion (HDFF), which combines two powerful features and utilizes tensor fusion and multilinear subspace learning to improve the accuracy of pedestrian image identification.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Wenning Hu, Ming He, Xirui Chen, Nianbin Wang
Summary: This paper proposes a new representation learning method (RLF), which learns long-term dynamics using graph neural networks and trains the representation network based on a new state metric inspired by bisimulation relation. Experiments show that RLF can mine more stable state embeddings in continuous control tasks, and the learned policy on top of the embeddings has higher sample efficiency, performance, and generalization capability.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Sarbast Moslem
Summary: This study provides a sustainable and efficient solution for improving the public bus transport system in Dublin city. By attracting private car users, it aims to reduce CO2 emissions, minimize traffic congestions, and maximize commuter satisfaction. Using the parsimonious analytic hierarchy process model, the study evaluates uncertainty and decision maker scoring, providing consistent and reliable results.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Jun Li, Lanlan Jiang, Guimin Huang, Jingwei Zhang
Summary: The new coronavirus COVID-19 has caused great disaster worldwide, and China has effectively controlled the situation. This paper collected Chinese microblogs, forums, and online comments to conduct a sentiment analysis of the latest comments about COVID-19. By integrating the semantics of words, the accuracy of sentiment analysis was substantially improved.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Marios Krestenitis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Konstantinos Ioannidis, Elias B. Kosmatopoulos, Stefanos Vrochidis
Summary: This paper addresses the issue of informative path planning for a UAV used in precision agriculture. By using a non-uniform scanning approach, the time spent in areas with minimal value is reduced, while maintaining high precision in information-dense regions. A novel active sensing and deep learning-based coverage path planning approach is proposed, which adjusts the UAV's speed based on the quantity and confidence level of identified plant classes.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Haifei Peng, Jian Long, Cheng Huang, Shibo Wei, Zhencheng Ye
Summary: This paper proposes a novel multi-modal hybrid modeling strategy (GMVAE-STA) that can effectively extract deep multi-modal representations and complex spatial and temporal relationships, and applies it to industrial process prediction.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2024)
Article
Automation & Control Systems
Adrien Le Reun, Kevin Subrin, Anthony Dubois, Sebastien Garnier
Summary: This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Weiming Ba, Jung-Che Chang, Jing Liu, Xi Wang, Xin Dong, Dragos Axinte
Summary: This paper proposes a hybrid scheme for kinematic control of continuum robots, which avoids errors through tension supervision and accurate piecewise linear approximation. The effectiveness of the controller is verified on different continuum robotic systems.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaoxuan Cui, Fangzhou Liu, Hildeberto Jardon-Kojakhmetov, Ming Cao
Summary: This paper studies a discrete-time time-varying multi-layer networked SIWS model with multiple resources under both single-virus and competing multi-virus settings. The research provides a comprehensive analysis of the system's behavior and equilibrium points in the single-virus and multi-virus cases.
Article
Automation & Control Systems
Ruixu Wu, Xianbin Wen, Liming Yuan, Haixia Xu, Yanli Liu
Summary: In this paper, a new tracking method based on deformable Transformer and spatiotemporal information is proposed, which achieves better tracking performance by fusing local and global features and extracting spatiotemporal information. The experiments show that the proposed method outperforms the baseline method on multiple benchmark datasets, and the simplified model structure achieves a higher frame rate.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
