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2024 International Conference Automatics and Informatics, ICAI 2024

作者： Mihalev, Georgi Yordanov, Stanimir Ormandzhiev, Krasimir Technical University of Gabrovo Information and Control Systems Department of Automation Gabrovo Bulgaria Technical University of Gabrovo Department of Power Engineering Gabrovo Bulgaria

ISBN: (纸本)9798350353907

The paper proposes a switching multi-regulator control for an electro-hydraulic servo system with throttle regulation. The architecture of the multi-regulator control, composed of three conventional regulators (PID1, PI2, PI3) for different regions of the setpoint signal variation and switching logic, is discussed. The main issues arising from the use of such control are considered, and an analysis of the stability of the closed-loop system is conducted. Some mathematical formulas and descriptions are presented. Using a universal measurement and control module, graphical results for the quality of the designed control are obtained. The advantages of this type of control and the emergence of additional robust qualities of the system are experimentally proven. © 2024 IEEE.

关键词： Hydraulic servomechanisms

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Simulation Method for Reliability Prediction of Switching Power Supply injected with PoF Model 6

Simulation Method for Reliability Prediction of Switching Po...

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6th International Conference on System Reliability and Safety engineering, SRSE 2024

作者： Xiao, Kaiwen Chen, Cen Liu, Weiming Wang, Shujuan Gao, Xiaoying Zhai, Guofu Harbin Institute of Technology Department of Electrical Engineering & Automation Harbin China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9798350356083

Switching power supplies are widely used in aerospace, new energy and many other fields. During long-term operation, various electronic components in these supplies experience performance degradation due to continuous electrical and thermal stress, leading to changes in output characteristics. This is the fundamental reason affecting the reliability of switching power supplies. However, the current combination of physics of failure (PoF) models and simulation technique is imperfect, and most methods cannot achieve batch injection of multiple device failures. This paper proposes a reliability prediction simulation method for switching power supplies based on PoF model injection. By focusing on a switching circuit, the approach involves digital twin modeling and validation, failure mechanism and sensitivity analysis, key failure components degradation modeling, and batch degradation simulation. This method achieves continuous degradation data of multiple components based on the PoF model through batch injection, improving the efficiency and accuracy of reliability prediction for switching power supplies. © 2024 IEEE.

关键词： Sensitivity analysis

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Application of a Modified Multiparametric PID controller for control of an Electrohydraulic Servo System

Application of a Modified Multiparametric PID Controller for...

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2024 International Conference Automatics and Informatics, ICAI 2024

作者： Yordanov, Stanimir Mihalev, Georgi Ormandzhiev, Krasimir Ivanov, Stefan Technical University of Gabrovo Information and Control Systems Department of Automation Gabrovo Bulgaria Technical University of Gabrovo Department of Power Engineering Gabrovo Bulgaria

ISBN: (纸本)9798350353907

The paper proposes a switching multiparametric control for an electrohydraulic servo system with throttle regulation. The architecture of a MISO (Multiple Input Single Output) control is considered, consisting of a conventional PID controller operating in the deviation control channel and a fuzzy PID controller operating in the disturbance channel. The main issues arising from the use of this type of control are discussed, and an analysis of the stability of the closed-loop system is conducted. Graphic results for the control quality of the designed system are obtained using a universal measurement and control module. The advantages of this type of control and the manifestation of additional robust qualities of the system are experimentally demonstrated. © 2024 IEEE.

关键词： Three term control systems

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Path Planning Using Improved Hybrid A∗ Algorithm for Mobile Robots 25

Path Planning Using Improved Hybrid A∗ Algorithm for Mobile...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Cheng, Zikang Xue, Jingbo Wang, Bo Dong, Guangzhong Wei, Jingwen Chen, Chunlin Nanjing University Department of Control Science and Intelligence Engineering Naning China Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350366600

The Hybrid A∗ algorithm is suitable for Ackermann-type mobile robots with nonholonomic constraints. However, in practical path planning, such issues as long search times, inefficient search efficiency, and excessive planning path changes causing unstable robot motion still exist. To improve the effectiveness of path planning, this paper optimizes the Hybrid A∗ algorithm by using variable search step size and designing a path evaluation function during node expansion. Path planning experiments are conducted based on simulation and physical experimental platforms. The results show that the improved algorithm reduces the search nodes and planning time, effectively enhancing the algorithm's search performance and efficiency. In addition, it avoids pose errors caused by reverse driving, ensuring the priority and smoothness of forward driving, and achieves efficient and stable path planning for Ackermann-type mobile robots. © 2024 IEEE.

关键词： Mobile robots

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Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food

Stability and bifurcation analysis of delayed tri-trophic fo...

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作者： Ramasamy, Sivasamy Banjerdpongchai, David Park, PooGyeon Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electrical Engineering Pohang University of Science and Technology Pohang Korea Republic of

One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of additional food to predators in a delayed tri-trophic food chain model, where interference among the species is determined by Holling type-II functional response. The proposed model incorporates the fact that the growth rates of prey and middle predators are decreased due to the fear of middle and special predators, respectively. The additional food is supplied to both predators by either nature or external agencies. Furthermore, the poisoned prey in the predator's environment is taken into account. In the proposed model, we use two time delays: one for the growth term of the middle predator and another for the gestation delay of the special predator. We determine the conditions for the existence of ecologically feasible equilibrium points and their local and global stability. In addition, we establish the conditions for the existence of Hopf bifurcation around interior equilibrium to seek periodic behavior in nondelayed and delayed models. Numerical investigations are performed to justify the proposed theoretical findings through phase portraits, time series of solutions, and bifurcation diagrams. We observe that the chaotic dynamics of a tri-trophic food chain model can be controlled by the proper choice of the fear effect and by supplying additional food parameters. As a result, our findings provide more ecological insights into the dynamics of the delayed tri-trophic food chain model with the fear effect and additional food supply. © 2023 John Wiley & Sons, Ltd.

关键词： Hopf bifurcation

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Uncertainty and its Effect on Optimal Multidrug control of Hemodynamic Variables

Uncertainty and its Effect on Optimal Multidrug Control of H...

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2024 American control Conference, ACC 2024

作者： Popescu, Teodora Birs, Isabela R. Othman, Ghada Ben Yumuk, Erhan Mihai, Marcian Hegedus, Erwin Copot, Dana De Keyser, Robin Ionescu, Clara M. Muresan, Cristina I. Technical University of Cluj-Napoca Department of Automation Cluj-Napoca Romania Ghent University Research Group on Dynamical Systems and Control Department of Electromechanics Systems and Metal Engineering Tech Lane Science Park 125 Gent9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Maslak Istanbul34469 Turkey

ISBN: (纸本)9798350382655

Computer aided control in biomedical applications is gaining more and more popularity due to numerous research studies that have proven the efficiency of automatic control over manual dosing, which is highly susceptible to human errors. Optimal drug dosing is best achieved using automatic control, which triggers important benefits in terms of both costs and patient side-effects. However, mathematical models for patients are highly susceptible to large modeling uncertainty. A predictive control algorithm is designed in this paper for optimal multidrug control of hemodynamic variables. Improved closed loop performance is obtained compared to similar control strategies, for ± 30% modeling uncertainty. The simulation results demonstrate that predictive control is a feasible solution for optimal drug dosing. An analysis of the closed loop performance for significant patient variability shows that controllers tuned using a nominal patient model often fail to achieve desired robustness. To limit the effect of modeling uncertainty, the prediction model should be updated using an online identification tool to extract patient features. © 2024 AACC.

关键词： Predictive control systems

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Data-driven consensus control of fully distributed event-triggered multi-agent systems

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Science China(Information Sciences) 2023年第5期66卷 147-161页

作者： Yifei LI Xin WANG Jian SUN Gang WANG Jie CHEN School of Automation Beijing Institute of Technology The State Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This study investigates the consensus control issue in discrete-time linear multi-agent systems(MASs) using data-driven control under undirected communication networks. To alleviate the communication burden, an adaptive event-triggered control strategy involving only local information is proposed and a model-based stability condition is derived that guarantees the asymptotic consensus of MASs. Furthermore,a data-based consensus condition for unknown MASs is established by combining a data-based system representation with the model-based stability condition, using only pre-collected noisy input-state data instead of the accurate system information a priori. Specifically, both model-based and data-driven event-triggered controllers can be utilized without requiring any global information. The validity and correctness of the controllers and associated theoretical results are demonstrated via numerical simulations.

关键词： distributed control event-triggered control data-driven control discrete-time MASs

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A Real-Time Semantic Segmentation Method Based on Transformer for Autonomous Driving

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Computers, Materials & Continua 2024年第12期81卷 4419-4433页

作者： Weiyu Hao Jingyi Wang Huimin Lu Donald Bren School of Information and Computer Sciences University of CaliforniaIrvineCA 92612USA Department of Control Engineering Kyushu Institute of TechnologyKitakyushu804-8550Japan School of Automation Southeast UniversityNanjing210096China

While traditional Convolutional Neural Network(CNN)-based semantic segmentation methods have proven effective,they often encounter significant computational challenges due to the requirement for dense pixel-level predictions,which complicates real-time *** address this,we introduce an advanced real-time semantic segmentation strategy specifically designed for autonomous driving,utilizing the capabilities of Visual *** leveraging the self-attention mechanism inherent in Visual Transformers,our method enhances global contextual awareness,refining the representation of each pixel in relation to the overall *** enhancement is critical for quickly and accurately interpreting the complex elements within driving sce-narios—a fundamental need for autonomous *** experiments conducted on the DriveSeg autonomous driving dataset indicate that our model surpasses traditional segmentation methods,achieving a significant 4.5%improvement in Mean Intersection over Union(mIoU)while maintaining real-time *** paper not only underscores the potential for optimized semantic segmentation but also establishes a promising direction for real-time processing in autonomous navigation *** work will focus on integrating this technique with other perception modules in autonomous driving to further improve the robustness and efficiency of self-driving perception frameworks,thereby opening new pathways for research and practical applications in scenarios requiring rapid and precise decision-making *** experimentation and adaptation of this model could lead to broader implications for the fields of machine learning and computer vision,particularly in enhancing the interaction between automated systems and their dynamic environments.

关键词： Visual transformer semantic segmentation autonomous driving

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One-Variable Attack on the Industrial Fault Classification System and Its Defense

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engineering 2022年第12期19卷 240-251页

作者： Yue Zhuo Yuri A.W.Shardt Zhiqiang Ge State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Department of Automation Engineering Technische Universität IlmenauIlmenau D-98684Germany

Recently developed fault classification methods for industrial processes are mainly ***,models based on deep neural networks have significantly improved fault classification accuracy owing to the inclusion of a large number of data ***,these data-driven models are vulnerable to adversarial attacks;thus,small perturbations on the samples can cause the models to provide incorrect fault *** recent studies have demonstrated the vulnerability of machine learning methods and the existence of adversarial *** paper proposes a black-box attack method with an extreme constraint for a safe-critical industrial fault classification system:Only one variable can be perturbed to craft adversarial ***,to hide the adversarial samples in the visualization space,a Jacobian matrix is used to guide the perturbed variable selection,making the adversarial samples in the dimensional reduction space invisible to the human *** the one-variable attack(OVA)method,we explore the vulnerability of industrial variables and fault types,which can help understand the geometric characteristics of fault classification *** on the attack method,a corresponding adversarial training defense method is also proposed,which efficiently defends against an OVA and improves the prediction accuracy of the *** experiments,the proposed method was tested on two datasets from the Tennessee–Eastman process(TEP)and steel plates(SP).We explore the vulnerability and correlation within variables and faults and verify the effectiveness of OVAs and defenses for various classifiers and *** industrial fault classification systems,the attack success rate of our method is close to(on TEP)or even higher than(on SP)the current most effective first-order white-box attack method,which requires perturbation of all variables.

关键词： Adversarial samples Black-box attack Industrial data security Fault classification system

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Fusing Multi-scale Binary Convolution with Joint Attention Face Expression Recognition Algorithm 19th

Fusing Multi-scale Binary Convolution with Joint Attention ...

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19th Chinese Intelligent Systems Conference, CISC 2023

作者： Qin, Minbo Li, Lin Automation Division Department of Control Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9789819968855

Addressing the challenges of wild facial expression datasets being affected by illumination and pose variations, and the expression features being dispersed across multiple easily overlooked facial regions, this paper proposes a facial expression recognition network called Binary and Joint Attention Network. Firstly, The multi-scale binary convolution module integrates texture features of different granularities. Subsequently, the proposed Multi-head Joint Attention module focusing on multiple distinct facial areas through multiple attention heads. Lastly, the inter-attention map loss is designed to prevent attention overlap while assisting in classification. Experimental results on multiple datasets, including SFEW2.0, RAF-DB, FER2013, demonstrate that the proposed network can effectively recognize various facial expressions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Local binary pattern

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