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Modular Model Reduction of Interconnected Systems: A Top-Down Approach

IFAC-PapersOnLine 2023年第2期56卷 4246-4251页

作者： Lars A.L. Janssen Bart Besselink Rob H.B. Fey Nathan van de Wouw Dynamics and Control group Department of Mechanical Engineering Eindhoven University of Technology Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen

Complex systems often involve interconnected subsystem models developed by multi-disciplinary teams. To simulate and control such systems, a reduced-order model of the interconnected system is required. In the scope of this paper, we pursue this goal by subsystem reduction to warrant modularity of the reduction approach. However, reducing subsystem models affects not only the subsystems accuracy, but also the interconnected model accuracy, making it difficult to predict a priori the accuracy impact of subsystem reduction. To address this challenge, we introduce a top-down approach using mathematical tools from robust performance analysis, enabling the translation of accuracy requirements from the interconnected model to the subsystem level. This enables independent subsystem reduction while ensuring the desired accuracy of the interconnected model. We demonstrate the effectiveness of our approach through a structural dynamics case study.

关键词： Complex systems Model reduction control of interconnected systems Robust performance Top-down approach Error bounds

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Design and testing of Hybrid Slime Mold Algorithm for Real-Time Adaptive Mobile Robot Path Planning in Dynamic Environments

Design and testing of Hybrid Slime Mold Algorithm for Real-T...

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Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Sachin Gupta Shivali Gupta Shaik Mohammed Raith Anand Kumar Salil Bharany Vishnu Kant Ch.Sandeep Department of Robotics and Control Engineering School of Electronics and Control Engineering Lovely Professional University Phagwara India Department of Chemistry School of Chemical Engineering and Physical Sciences Lovely Professional University Phagwara India Department of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Chitkara University Institute of Engineering and Technology Chitkara University Rajpura India School of Computer Science and Artificial Intelligence SR University Warangal Telangana

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Dynamic path planning and collision prevention is one of the key tasks for autonomous vehicles in relation to dynamic movement of obstacles. In this paper, a novel hybrid approach based on integration of Slime Mold Algorithm (SMA), Triangle Inequality Principle (TIP), and Partition Method Strategy (PMS) for solution of this problem statement. The SMA algorithm is very flexible and adaptive by nature due to its biological working mechanism which is associated with TIP and PMS strategies in relation to their optimization and efficient path planning capabilities and robust solutions. This integrated module is tested in virtual environment and the results are compared with other updated algorithms such as A*, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) for the same static and dynamic environment. It has been observed from the results that this hybrid strategy significantly improves the path planning task several times than other algorithms in terms of multiple aspects. Under testing conditions, the path length was reduced to 25% than other algorithms in a dynamic environment. During this calculation, the computational efficiency of the system has been improved to 60% than conventional methods. The chances of collision have been improved to 34.23% especially in environment where the obstacles are moving. The capability of SMA has been improved due to the synergy between TIP and PMS. The dynamic and adaptive nature of this algorithm is suitable for various applications such as search-and-rescue operations, manufacturing units’ automation and other hazardous environment exploration.

关键词： Navigation Heuristic algorithms Virtual environments Path planning Partitioning algorithms Safety Mobile robots Vehicle dynamics Testing Genetic algorithms

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Dissipative Avoidance Feedback for Reactive Navigation Under Second-Order Dynamics

arXiv

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arXiv 2024年

作者： Smaili, Lyes Tang, Zhiqi Berkane, Soulaimane Hamel, Tarek Department of Computer Science and Engineering University of Quebec in Outaouais GatineauQC Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden Department of Electrical Engineering Lakehead University ON Canada France

This paper addresses the problem of autonomous robot navigation in unknown, obstacle-filled environments with second-order dynamics by proposing a Dissipative Avoidance Feedback (DAF). Compared to the Artificial Potential Field (APF), which primarily uses repulsive forces based on position, DAF employs a dissipative feedback mechanism that accounts for both position and velocity, contributing to smoother and more natural obstacle avoidance. The proposed continuously differentiable controller solves the motion-to-goal problem while guaranteeing collision-free navigation by using the robot’s state and local obstacle distance information. We show that the controller guarantees safe navigation in generic n-dimensional environments and that all undesired ω-limit points are unstable under certain controlled curvature conditions. Designed for real-time implementation, DAF requires only locally measured data from limited-range sensors (e.g., LiDAR, depth cameras), making it particularly effective for robots navigating unknown workspaces. Simulations in 2D and 3D environments are conducted to validate the theoretical results and to showcase the effectiveness of our approach. © 2024, CC BY.

关键词： Feedback

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Resilient Cooperative control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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UniQuad: A Unified and Versatile Quadrotor Platform Series for UAV Research and Application

arXiv

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arXiv 2024年

作者： Zhang, Yichen Chen, Xinyi Liu, Peize Wang, Junzhe Zou, Hetai Pan, Neng Gao, Fei Shen, Shaojie The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China Huzhou Institute Zhejiang University Huzhou China

As quadrotors take on an increasingly diverse range of roles, researchers often need to develop new hardware platforms tailored for specific tasks, introducing significant engineering overhead. In this article, we introduce the UniQuad series, a unified and versatile quadrotor platform series that offers high flexibility to adapt to a wide range of common tasks, excellent customizability for advanced demands, and easy maintenance in case of crashes. This project is fully open-source at https://***/UniQuad. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities

arXiv

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arXiv 2024年

作者： Hu, Senkang Fang, Zhengru Deng, Yiqin Chen, Xianhao Fang, Yuguang The Department of Computer Science City University of Hong Kong Hong Kong The School of Control Science and Engineering Shandong University Jinan China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current autonomous driving systems are mostly based on a single vehicle, which has significant limitations which still poses threats to driving safety. Collaborative perception with connected and autonomous vehicles (CAVs) shows a promising solution to overcoming these limitations. In this article, we first identify the challenges of collaborative perception, such as data sharing asynchrony, data volume, and pose errors. Then, we discuss the possible solutions to address these challenges with various technologies, where the research opportunities are also elaborated. Furthermore, we propose a scheme to deal with communication efficiency and latency problems, which is a channel-aware collaborative perception framework to dynamically adjust the communication graph and minimize latency, thereby improving perception performance while increasing communication efficiency. Finally, we conduct experiments to demonstrate the effectiveness of our proposed scheme. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Reinforcement Learning-Based Output Stabilization control for Nonlinear Systems With Generalized Disturbances

Reinforcement Learning-Based Output Stabilization Control fo...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Zezhi Tang J Anthony Rossiter Yi Dong George Panoutsos Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Electronics and Computer Science University of Southampton Southampton United Kingdom

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

This paper proposes a new disturbance observer (DO)-based reinforcement learning (RL) control approach for nonlinear systems with unmatched (generalized) disturbances. While a nonlinear disturbance observer (NDO) is utilized to measure the plant uncertainties, disturbances can exist in the plant via distinct channels from those of the control signals; so-called mismatched disturbances are theoretically difficult to attenuate within the channel of the system's states. A generalized disturbance observer-based compensator is implemented to address the uncertainty cancellation problem by removing the influence of uncertainties from the output channels. Con-currently, a composite actor-critic RL scheme is utilized for approximating the optimal control policy as well as the ideal value function pertaining to the compensated system by solving a Hamilton-Jacobi-Bellman (HJB) equation for both online and offline iterations simultaneously. Stability analysis verifies the convergence of the proposed framework. Simulation results are included to illustrate the effectiveness of the proposed scheme.

关键词： Uncertainty Simulation Measurement uncertainty Optimal control Estimation Reinforcement learning Disturbance observers

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Machine Learning Based Intrusion Detection System in Cloud Environment 8

Machine Learning Based Intrusion Detection System in Cloud E...

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8th International Conference on Information Technology and Nanotechnology, ITNT 2022

作者： Saeed, Muhammad Salman Saurabh, Raman Bhasme, Sarang Balasaheb Nazarov, Alexey N. Moscow Institute of Physics and Technology Department of Radio Engineering and Cybernetics Moscow Russia Federal Research Center Computer Science and Control of Russian Academy of Sciences Moscow Russia

ISBN: (数字)9781665485715

ISBN: (纸本)9781665485715

Attacks and intrusions on computer networks often have different characteristics and behaviors that require professional help. The number of attacks is growing in line with the development of computer networks. In fact, expert knowledge is declining over time and should be reviewed and made available in the system, making it necessary to hire an experienced person. Cloud computing is an advancement in IT technologies that provide users with the most up-To-date, highly sought-After virtual services with high flexibility, low infrastructure costs, and minimal maintenance. Protection against network intruders is one of the most important security challenges for cloud computing, as it affects the privacy, availability, and integrity of cloud services. Because cloud computing is a shared environment, it can be vulnerable to various threats. Because building strong access systems are essential to maintaining cloud security, but it remains an obscure goal and a major challenge due to the growing number of cyber-Attacks. In this study, a machine-learning based approach was used to propose an intrusion detection system (IDS) based on a network based cloud computing model. During the previous processing phase, we used a feature selection algorithm from the CICDDoS2019 database to select features. We have used the Naive Bayes Classifier, Decision Tree Classifier, Supporting Classifier, Logistic Regression, and Random Forest Classifier, all of which are well-known categories. Simulation results when compared to these five different classifiers, random forest algorithm show improvements in overall accuracy, precision, recall and F1 score. We explain how various characteristics of machine learning techniques can be used to build efficient IDS. The goal of this research is to develop a new method based on intrusion detection systems and their varied designs for improving intrusion detection accuracy in cloud computing. © 2022 IEEE.

关键词： Decision trees

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A Framework for Analyzing GPU-Executed Malware 23

A Framework for Analyzing GPU-Executed Malware

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Apostol, Teodor-Petrut Velea, Radu Deaconescu, Razvan University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Romania

ISBN: (纸本)9781665439398

Graphics processing units (GPU) are an integral part of today's computing environment. The marketing emphasis on user experience pushes vendors to constantly look for better graphics hardware and newer drivers to integrate into their products. Most commodity GPUs function as accelerators for image and video processing tasks and are present (either as dedicated or integrated form factor) in everyday devices including desktops, laptops, smartphones or other portable gadgets. Recent trends have seen the GPU move to perform additional tasks such as offloading some of the computation from the CPU or solve highly parallel problems. As GPUs become more powerful and widespread they will naturally become a very attractive target for attackers. Cybercriminals will look for any vulnerability in the GPU hardware or software, and will try to use it as an attack vector to compromise the system. This paper presents some of the incidents that involve the use of GPUs to perform malicious actions and proposes a framework to allow analysts to inspect the code executed on the GPU and trigger security alerts. The proposed solution will look at the processes running inside an operating system, it will identify which of them require access to the GPU and will try to intercept and scan for any suspicious activities, similar to a conventional security solution. © 2021 IEEE.

关键词： Graphics processing unit

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Real-Time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing

Real-Time Trajectory Generation via Dynamic Movement Primiti...

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American control Conference (ACC)

作者： Catherine Weaver Roberto Capobianco Peter R. Wurman Peter Stone Masayoshi Tomizuka Sony AI Department of Mechanical Engineering University of California Berke-ley CA USA Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Computer Science The University of Texas at Austin TX USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We employ sequences of high-order motion primitives for efficient online trajectory planning, enabling competitive racecar control even when the car deviates from an offline demonstration. Dynamic Movement Primitives (DMPs) utilize a target-driven nonlinear differential equation combined with a set of perturbing weights to model arbitrary motion. The DMP's target-driven system ensures that online trajectories can be generated from the current state, returning to the demonstration. In racing, vehicles often operate at their handling limits, making precise control of acceleration dynamics essential for gaining an advantage in turns. We introduce the Acceleration goal (Acc. goal) DMP, extending the DMP's target system to accommodate accelerating targets. When sequencing DMPs to model long trajectories, our Acc. goal DMP explicitly models acceleration at the junctions where one DMP meets its successor in the sequence. Applicable to DMP weights learned by any method, the proposed DMP generates trajectories with less aggressive acceleration and jerk during transitions between DMPs compared to second-order DMPs. Our proposed DMP sequencing method can recover from trajectory deviations, achieve competitive lap times, and maintain stable control in autonomous vehicle racing within the high-fidelity racing game Gran Turismo Sport. Video available: https://***/***/racingdmp/home

关键词： Sequential analysis Trajectory planning Dynamics Games Streaming media Real-time systems Trajectory

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