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arXiv 2023年

作者： Gong, Xin Liang, Yiwen Cui, Yukang Liang, Shi Huang, Tingwen The Department of Mechanical Engineering The University of Hong Kong Pokfulam Road Hong Kong The College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Texas A&M University at Qatar Doha23874 Qatar

This paper studies the problem of cooperative control of heterogeneous multi-agent systems (MASs) against Byzantine attacks. The agent affected by Byzantine attacks sends different wrong values to all neighbors while applying wrong input signals for itself, which is aggressive and difficult to be defended. Inspired by the concept of Digital Twin, a new hierarchical protocol equipped with a virtual twin layer (TL) is proposed, which decouples the above problems into the defense scheme against Byzantine edge attacks on the TL and the defense scheme against Byzantine node attacks on the cyber-physical layer (CPL). On the TL, we propose a resilient topology reconfiguration strategy by adding a minimum number of key edges to improve network resilience. It is strictly proved that the control strategy is sufficient to achieve asymptotic consensus in finite time with the topology on the TL satisfying strongly (2f + 1)-robustness. On the CPL, decentralized chattering-free controllers are proposed to guarantee the resilient output consensus for the heterogeneous MASs against Byzantine node attacks. Moreover, the obtained controller shows exponential convergence. The effectiveness and practicality of the theoretical results are verified by numerical examples. © 2023, CC BY.

关键词： Multi agent systems

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Application of Machine Learning Models for Predicting Students' Performance in Mathematics: A K-Fold Approach

Application of Machine Learning Models for Predicting Studen...

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Science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Felix Ale Ikpaya D. Ikpaya Ilesanmi Danyan Goodness O. Opateye Gregory Onwodi Olufemi O. Agboola Department of Engineering & Space Systems National Space Research & Development Agency Abuja Nigeria Ground Station & Mission Control National Space Research & Development Agency Abuja Nigeria Department of Mechanical & Mechatronics Engineering Achievers University Owo Nigeria Department of Computer Science National Open University of Nigeria Abuja Nigeria

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

Mathematics plays a pivotal role in science, technology and engineering. It is one of the compulsory subjects to gain admission into a higher institution in Nigeria. Considering its importance, students' performance has been a significant concern for most educators, government, parents and guardians. This study aims to predict students' performance in mathematics using the K-fold approach to support effective decision-making and policy implementation on mathematics. The primary dataset was collected from 192 senior secondary schools, and one mathematics student was randomly selected from five Senior Secondary Schools in Bwari Area Council, Abuja, and used as a sample. Students' Mathematics Achievement Test (SMAT) was used as the instrument to collect data. The data was processed and modelled using the Python Programming language. Thus, five machine learning models were trained and evaluated to overcome overfitting using four-, five---, and six-fold K-Fold cross-validation techniques. Five folds performed best for all the models except for the Support Vector Regressor, which performed best with six folds. The evaluation of the models showed that the Light Gradient Boosting Model outperformed others with a Mean Absolute Error of 12.642 and a Root Mean Square Error of 15.894. The models were significantly influenced by the students' personal study time, friends' assistance, and the parents' educational background. It is therefore recommended that academic researchers, educational authorities in Nigeria, and relevant stakeholders use and improve on this model to predict the students' scores and assist them in achieving great performance in mathematics.

关键词： Instruments Predictive models Mathematics Mathematical models Vectors Stakeholders Sustainable development

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Performance Evaluation of a Three-Phase PV Power Plant under Unbalanced Conditions with Islanding Detection Reliability Test

Performance Evaluation of a Three-Phase PV Power Plant under...

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Compatibility in Power Electronics (CPE)

作者： Anas Abdullah Alvi Enrique Romero-Cadaval Eva González-Romera Dmitri Vinnikov Jamil Hassan Department of Electrical Electronic and Control University of Extremadura Badajoz Spain Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia Department of R&D and Innovation SEnergy Products & Services Badajoz Spain

The use of renewable energy is increasing ever so highly during this modern age of technology. The use of wind, solar and hydro energy is rising rapidly in the world due to the less emissions of harmful gases in the atmosphere. Since the energy produced from these sources like wind and solar energy is increasing a lot, the use of grid connected inverters is also expanding. Deep analysis of these inverters’ operation is important when working in non-ideal situations. The main aim of this paper is to analyze the operation of a three-phase photovoltaic power plant (rated at 250 kW) supplying power to both three-phase and single-phase loads. The analysis covers both, connected and disconnected modes and also includes the performance of a basic islanding detection method considering voltage and frequency deviation of the phase locked loop (PLL) at the Point of Common Coupling (PCC) and the effect on the whole system considering unbalanced situations with different values of irradiances is observed. The novelty of this paper is to identify a case in which the islanding detection fails due to the connection of a single-phase load in the point of low voltage.

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

A Multi-Player Potential Game Approach for Sensor Network Lo...

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IEEE Conference on Decision and control

作者： Gehui Xu Guanpu Chen Baris Fidan Yiguang Hong Hongsheng Qi Thomas Parisini Karl H. Johansson Department of Electrical and Electronic Engineering Imperial College London London UK Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Control Science and Engineering Tongji University shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies.

关键词： Location awareness Noise Games Position measurement Nash equilibrium Distance measurement Noise measurement

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Improving Road Safety With Enhanced Vehicle Detection for Night-time Traffic in Mirpur

Improving Road Safety With Enhanced Vehicle Detection for Ni...

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International Conference on Robotics and Artificial Intelligence (ICRAI)

作者： Usama Younis Faisal Riaz Umar Raza Gokhan Atali Hamid Rabnawaz Control Automotive and Robotics Lab Affiliated Lab of National Centre of Robotics and Automation (NCRA) HEC Islamabad Pakistan Department of Engineering Manchester Metropolitan University Manchester United Kingdom Mechatronics Engineering Sakarya University of Applied Sciences Sakarya Turkey Selftech Pvt Ltd

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

This paper presents a study on improving night-time vehicle detection in the Mirpur region through a modified neural network model. Given the challenges of low visibility at night, the research focused on optimizing a deep learning algorithm to enhance detection accuracy. A dataset of 10,000 images covering various vehicle types was collected and annotated to train and test the model. The study found a 7% increase in detection performance compared to the standard model, highlighting the potential for tailored algorithms in specific environmental conditions. The findings suggest significant implications for road safety and autonomous driving systems, particularly in regions with similar night-time driving challenges. The research contributes to the broader field of computer vision by showing the effectiveness of model optimization in real-world conditions.

关键词： Accuracy Computational modeling Vehicle detection Neural networks Road safety Reliability Robotics and automation Optimization Autonomous vehicles Standards

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Invisible Servoing: a Visual Servoing Approach with Return-Conditioned Latent Diffusion

arXiv

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arXiv 2024年

作者： Gerges, Bishoy Bazzana, Barbara Botteghi, Nicolò Aboudorra, Youssef Franchi, Antonio Robotics and Mechatronics Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede7500AE Netherlands Department of Applied Mathematics University of Twente Enschede7500AE Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy

In this paper, we present a novel visual servoing (VS) approach based on latent Denoising Diffusion Probabilistic Models (DDPMs). Opposite to classical VS methods, the proposed approach allows reaching the desired target view, even when the target is initially not visible. This is possible thanks to the learning of a latent representation that the DDPM uses for planning and a dataset of trajectories encompassing target-invisible initial views. The latent representation is learned using a Cross-Modal Variational Autoencoder, and used to estimate the return for conditioning the trajectory generation of the DDPM. Given the current image, the DDPM generates trajectories in the latent space driving the robotic platform to the desired visual target. The approach is applicable to any velocity-based controlled platform. We test our method with simulated and real-world experiments using generic multi-rotor Uncrewed Aerial Vehicles (UAVs). A video of our experiments can be found at https://***/yu-aTxqceOA. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Differential Flatness and Manipulation of Elasto-flexible Cables Carried by Aerial Robots in a Possibly Viscous Environment

Differential Flatness and Manipulation of Elasto-flexible Ca...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Chiara Gabellieri Antonio Franchi Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy LAAS-CNRS Université de Toulouse Toulouse France

This work considers a system composed of two quadrotors manipulating a deformable and extensible cable. The dynamic model is presented, and it is based on a discrete representation of the cable, which is decomposed into lumped masses interconnected by linear springs through passive spherical joints. A set of flat outputs is found for the system. The flatness is exploited to design a method to manipulate the cable, which is then tested through numerical simulations.

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Improving Wind Energy Conversion System Performance Via Fssosmc-Based Mppt with Neuro-Fuzzy Estimation and Vg-Reod

SSRN

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SSRN 2024年

作者： Ullah, Ameen Jianfei, Pan Ullah, Safeer Rahman, Tanzeel Ur Sami, Irfan Rahman, Ata Ur Khan, Shahbaz Ahmad College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Quaid-e-Azam College of Engineering & Technology Sahiwal57000 Pakistan College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China School of Electrical and Electronics Engineering Chung-Ang University Dongjak-gu Seoul06974 Korea Republic of

This paper presents a novel approach to improving the performance of Wind Energy Conversion Systems (WECS) in dealing with the intermittent nature of wind power sources, which often results in power generation and electricity demand mismatch. The proposed method employs a sophisticated Maximum Power Point Tracking (MPPT) strategy that uses Fast Smooth Second-Order Sliding Mode control (FSSOSMC) to achieve maximum power extraction despite the wind fluctuations. However, the effectiveness of MPPT/control strategies depends on the accurate knowledge of the system parameters, which are typically unavailable in practical scenarios. To address this challenge, this study employs an offline neuro-fuzzy algorithm that incorporates the Takagi-Sugeno-Kang (TSK) fuzzy inference system to enhance the performance and robustness of the MPPT/control system by precisely estimating uncertain and nonlinear drift terms in the control input. Additionally, to address issues related to speed estimation and the missing derivative of the generator shaft, this study used a Variable-Gain Robust Exact Output Differentiator (VG-REOD). This component ensures accurate determination of the shaft speed, contributing to the overall effectiveness of the proposed approach. A comprehensive comparison was conducted between the proposed strategy and alternative control techniques, such as super-twisting sliding mode control and feedback linearization control, under varying stochastic and deterministic wind speed profiles. The performance evaluation of the proposed method is extensively carried out through MATLAB/Simulink simulations, providing insights into its effectiveness in optimizing WECS operation under real-world conditions. © 2024, The Authors. All rights reserved.

关键词： Sliding mode control

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Event-Triggered Attitude controller Design for Unmanned Aerial Vehicles under Cyber Attacks

Event-Triggered Attitude Controller Design for Unmanned Aeri...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Seungyong Han Xuyang Guo Yongsik Jin Yongseob Lim Suneel Kumar Kommuri Korea Atomic Energy Research Institute Daejeon Republic of Korea Department of Control Science and Engineering Tongji University Shanghai China Electronics and Telecommunications Research Institute Daegu Republic of Korea Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology Daegu Republic of Korea Department of Electrical and Electronic Engineering Xi’an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

This paper proposes an event-triggered attitude controller design method for unmanned aerial vehicles (UAVs) under cyber attacks. Versatile UAVs are capable of transmitting the measurement or receiving control signals through network channels. In the controller design for such UAVs, it is required to consider two distinctive features. The first one is that the strategy of updating the control signal is important for saving the limited energy consumption. The other one is that the UAVs are vulnerably exposed to threats of malicious attacks through network channels. For enhanced energy efficiency and improved stability, the event-triggered mechanism (ETM) and the attitude controller are simultaneously designed. By utilizing Lyapunov- Krasovskii functionals (LKFs), the sufficient conditions for the co-design are derived in terms of linear matrix inequalities (LMIs). For a 3-degrees of freedom (DOF) quadcopter system, the simulation results are presented to validate the proposed attitude control method.

关键词： Sufficient conditions Attitude control Simulation Autonomous aerial vehicles Stability analysis Numerical models Resource management

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A Computationally Lightweight Safe Learning Algorithm

A Computationally Lightweight Safe Learning Algorithm

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IEEE Conference on Decision and control

作者： Dominik Baumann Krzysztof Kowalczyk Koen Tiels Paweł Wachel Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Information Technology Uppsala University Uppsala Sweden Department of Control Systems and Mechatronics Wrocław University of Science and Technology Wrocław Poland Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands

Safety is an essential asset when learning control policies for physical systems, as violating safety constraints during training can lead to expensive hardware damage. In response to this need, the field of safe learning has emerged with algorithms that can provide probabilistic safety guarantees without knowledge of the underlying system dynamics. Those algorithms often rely on Gaussian process inference. Unfortunately, Gaussian process inference scales cubically with the number of data points, limiting applicability to high-dimensional and embedded systems. In this paper, we propose a safe learning algorithm that provides probabilistic safety guarantees but leverages the Nadaraya-Watson estimator instead of Gaussian processes. For the Nadaraya-Watson estimator, we can reach logarithmic scaling with the number of data points. We provide theoretical guarantees for the estimates, embed them into a safe learning algorithm, and show numerical experiments on a simulated seven-degrees-of-freedom robot manipulator.

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