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检索条件"任意字段=IEEE/SMC International Conference on System of Systems Engineering"

共 216509 条记录，以下是361-370 订阅

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MPC of Uncertain Nonlinear systems with Meta-Learning for Fast Adaptation of Neural Predictive Models 20

MPC of Uncertain Nonlinear Systems with Meta-Learning for Fa...

引用

ieee 20th international conference on Automation Science and engineering (CASE)

作者： Yan, Jiaqi Chakrabarty, Ankush Rupenyan, Alisa Lygeros, John Swiss Fed Inst Technol Automat Control Lab Zurich Switzerland Mitsubishi Elect Res Labs Cambridge MA 02139 USA Zurich Univ Appl Sci ZHAW Ctr Artificial Intelligence Zurich Switzerland

ISBN: (纸本)9798350358513;9798350358520

In this paper, we consider the problem of reference tracking in uncertain nonlinear systems. A neural State-Space Model (NSSM) is used to approximate the nonlinear system, where a deep encoder network learns the nonlinearity from data, and a state-space component captures the temporal relationship. This transforms the nonlinear system into a linear system in a latent space, enabling the application of model predictive control (MPC) to determine effective control actions. Our objective is to design the optimal controller using limited data from the target system (the system of interest). To this end, we employ an implicit model-agnostic meta-learning (iMAML) framework that leverages information from source systems (systems that share similarities with the target system) to expedite training in the target system and enhance its control performance. The framework consists of two phases: the (offine) meta-training phase learns an aggregated NSSM using data from source systems, and the (online) meta-inference phase quickly adapts this aggregated model to the target system using only a few data points and few online training iterations, based on local loss function gradients. The iMAML algorithm exploits the implicit function theorem to exactly compute the gradient during training, without relying on the entire optimization path. By focusing solely on the optimal solution, rather than the path, we can meta-train with less storage complexity and fewer approximations than other contemporary meta-learning algorithms. We demonstrate through numerical examples that our proposed method can yield accurate predictive models by adaptation, resulting in a downstream MPC that outperforms several baselines.

关键词： Predictive control systems

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Predesigning RoF-Based Millimeter-Wave Access Sub-Network in Megapolis 5G Communication system

Predesigning RoF-Based Millimeter-Wave Access Sub-Network in...

引用

ieee international conference on Microwaves, Communications, Antennas, Biomedical engineering and Electronic systems (COMCAS)

作者： Belkin, Mikhail E. Zhukov, Leonid Sigov, Alexander S. MIREA Russian Technol Univ Vernadski Ave 78 Moscow 119454 Russia

ISBN: (纸本)9798350348194;9798350348187

In the paper, the results of the predesigning a RoF-Based Millimeter-Wave Access Sub-Network in a Megapolis 5G Cellular Communication system are presented and discussed. In order to put the study in a practical direction, the capital of the Russian Federation, the city of Moscow, was chosen as a realistic object under investigation. On its territory, one of the largest in terms of area and population, the Western administrative district, was selected, and within it, the municipal district of Ramenki, in which a fiber-wireless-configured network with wireless communication in the band of 37.0-43.5 GHz was predesigned.

关键词： 5th generation cellular telecommunication network small cell concept fiber-wireless architecture WDM-RoF technology radio communication in the millimeter wave range Moscow cellular telecommunications network predesign

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Design and Implementation of Cascaded Ant Colony Optimization Coupled with Sliding Mode Controller for Autonomous Cruise Control system

Design and Implementation of Cascaded Ant Colony Optimizatio...

引用

2023 ieee international conference on Energy Technologies for Future Grids, ETFG 2023

作者： Gulzar, Muhammad Majid Mughees Ahmed, Muhammad Shakoor, Adnan Khalid, Muhammad Department of Control & Instrumentation Engineering Dhahran31261 Saudi Arabia University of Central Punjab Department of Electrical Engineering Lahore Pakistan Electrical Engineering Department Dhahran31261 Saudi Arabia

ISBN: (纸本)9781665471640

Driving assist systems are being widely used in modern cars nowadays for safety, efficiency and comfort. These systems are used in cruise control, self-driving control and even obstacle avoidance. All these systems include a lot of sensors and radars, which work together and generate fast responses to manipulate the direction or speed of a car. The main objective of using this sort of technology is to reduce accidents by reducing stress on the driver by increasing comfort of travel. The aim of this research is to develop a controller for cruise control in vehicles that can help to reach the desired speed most accurately, quite fast and efficiently. The proposed Ant Colony Optimization coupled with Sliding Mode Controller (ACO & smc) used in this research is more accurate and robust that can help to tune the parameters in a way that the cruise control system gives a minimum error, stable results with the least possible disturbances. Later on, the results are also compared with already used state-of-the-art technologies implemented for cruise control to show the superiority of the proposed controller. © 2023 ieee.

关键词： Ant Colony Optimization (ACO) Autonomous Vehicles Cruise Control Sliding Mode Controller (smc)

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Multi-User Computation Offloading in Mobile Edge Computing with Hybrid Whale Optimization

Multi-User Computation Offloading in Mobile Edge Computing w...

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2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Bil, Jing Li, Ning Yuan, Haitao Zhang, Jia Zhou, MengChu College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

With the increasing amount of data and the need for real-time processing, Mobile Edge Computing (MEC) is growing rapidly, driving the shift from traditional cloud computing to distributed edge architectures. When offloading these applications with large amounts of data on mobile devices, a lot of computing and storage resources and high energy consumption are required. Yet, mobile devices' computing power, resource storage, and battery power are often limited and cannot meet these needs. To solve a computation offloading problem for joint optimization of time, cost, and energy, this work proposes an improved hybrid algorithm called Chaos and Lévy flights-based Whale Optimization Algorithm (CLWOA) to solve the multi-user offloading problem in an MEC-Cloud system. Each task is offloaded to local processors of mobile devices, edge servers, and cloud servers in proportion to jointly minimize the completion time, energy consumption, and total cost. Finally, compared with the whale optimization algorithm, lévy flight whale optimization algorithm, refined whale optimization algorithm, and chaos-based whale optimization algorithm, CLWOA reduces the weighted cost by 1.89%, 0.31%, 0.19%, and 0.42%, respectively. © 2024 ieee.

关键词： Mobile edge computing

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Comparison of Neural Network Models for Short-Term Load Forecasting

Comparison of Neural Network Models for Short-Term Load Fore...

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2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Surmon, Shinead Ahmad, Ahmad Xiao, Xun Mo, Huadong School of Engineering and Technology University of New South Wales Canberra Australia University of Otago Department of Mathematics and Statistics Dunedin New Zealand School of Systems and Computing University of New South Wales Canberra Australia

ISBN: (纸本)9781665410205

Balancing supply and demand is crucial for efficient energy distribution. To achieve it, accurate short-term electrical load forecasting is essential. This study investigates the applicability of various machine learning architectures for short-term load forecasting, using an NSW load dataset from the Australian Energy Market Operator. The key finding is the superior performance of a hybrid model, which integrates LSTM and GRU layers, on the NSW load dataset. This study demonstrates hybrid neural network models can significantly improve the accuracy and reliability of energy load predictions, thereby suggesting a viable pathway for enhancing future utility management practices. © 2024 ieee.

关键词： Neural network models

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A Survey on AI-Based Detection Methods of GPS Spoofing Attacks on UAVs 12

A Survey on AI-Based Detection Methods of GPS Spoofing Attac...

引用

12th ieee international conference on Intelligent systems, IS 2024

作者： Alabidy, Abdallah Zaben, Amr Abu-Sharkh, Osama M.F. Noman, Haitham Ameen King Abdullah Ii School of Engineering Princess Sumaya University for Technology Department of Computer Engineering Amman Jordan

ISBN: (纸本)9798350350982

Global Positioning system (GPS) spoofing attacks on unmanned aerial vehicles (UAVs) can cause severe consequences, including abnormal behavior, privacy breaches, safety hazards, financial losses, and national security risks. Hence, detecting and preventing GPS spoofing attacks on UAVs is paramount to ensure their safety and security. This survey paper explores the cutting-edge techniques based on artificial intelligence (AI) proposed in the literature for detecting GPS spoofing attacks on UAVs. We present an overview of the UAV navigation system and then delve into the concept of GPS spoofing, encompassing its various forms, such as soft and hard spoofing. Furthermore, we discuss the advantages of utilizing AI in developing detection methods compared to traditional approaches. Subsequently, we analyze the detection methods based on deep learning (DL) and machine learning (ML) proposed in the literature, evaluating their strengths and weaknesses whenever feasible. Our survey provides valuable insights for researchers and practitioners working in the fields of AI and UAV security with the target of developing more advanced and effective AI-based methods for GPS spoofing detection on UAVs. © 2024 ieee.

关键词： Global positioning system

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Research on Task Collaboration Over Heterogeneous Networks Based on Evolutionary Game Theory

Research on Task Collaboration Over Heterogeneous Networks B...

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2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Wu, Hongqian Deng, Hongzhong Li, Jichao Luo, Hankang College of Systems Engineering National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781665410205

With the increasing level of machine intelligence, the problem of collaboration among intelligent individuals in heterogeneous networks has become a focal point of research. Taking the task allocation of heterogeneous Unmanned Aerial Vehicle (UAV) swarms as an example, we study the game behavior of heterogeneous network based on task traction. To align with the autonomous and collaborative decision-making process of unmanned swarms, we construct a multi-party multi-strategy evolutionary game framework on heterogeneous networks, define local and global game payoff functions, and innovatively propose an Enhanced Moran Rule that integrates 'Pairwise updating' and 'Virtual Game' (PVG-EMR algorithm) to improve the task collaboration of UAV swarm. Experiments on various underlying communication network models show that the PVG-EMR algorithm proposed in our study can effectively plan the collaborative object of UAVs and ensure the appropriate assignment of tasks in the heterogeneous network, optimizing both local and global payoffs. Moreover, the algorithm exhibits robust performance. © 2024 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Simulation of the Human Arm Dynamics and Motor Control in Unstable Environments: A Comparison with Experimental Data

Simulation of the Human Arm Dynamics and Motor Control in Un...

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2023 ieee international conference on systems, Man, and Cybernetics, smc 2023

作者： Treichl, Tobias Institute of System Dynamics and Control German Aerospace Center Wessling Germany

ISBN: (纸本)9798350337020

The simulation of the human body dynamics offers a powerful way to investigate the interaction between humans and systems. This so-called physical human-machine interaction (HMI) is useful to consider during the development of new products like tools, cars or aircrafts, in order to increase comfort and safety. In this work, the Modelica Human Body Library is presented first. It is the only digital human mode (DHM) for physical HMI available in the multi-domain modeling language Modelica so far. The model considers the human body dynamics as well as the motor control of the limbs. A special feature of the model is the human inspired control scheme, which takes into account effects such as human reaction time and limb stiffness adaption. After an introduction to the DHM, its capabilities are evaluated by comparing simulation results with experimental data from a experimental study. In the study, different unstable force fields were applied to the hands of subjects as they approached a target. The resulting hand trajectories were measured. As many control tasks for humans, especially while using tools, are characterized by unstable behavior, this study is well suited to evaluate a DHM. Comparison with the experimental data shows that the resulting hand trajectories in the simulation are comparable to the ones the subjects produced due to the force fields. This applies for both, the initial tries with big deviations as well as the tries after the subjects adapted their arm stiffness to the force field. © 2023 ieee.

关键词： digital human model dynamic analysis human motor control physical human machine interaction

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Illusory Control with Instant Virtual World Environment

Illusory Control with Instant Virtual World Environment

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2023 ieee international conference on systems, Man, and Cybernetics, smc 2023

作者： Aoki, Junki Sasaki, Fumihiro Yamashina, Ryota Kurazume, Ryo Ricoh Company Ltd. Japan Graduate School of Information Science and Electrical Engineering Kyushu University Japan Kyushu University Faculty of Information Science and Electrical Engineering Japan

ISBN: (纸本)9798350337020

We proposed a teleoperation method, illusory control (IC), that provides a comfortable operation experience using a seamless transition between real and pre-prepared virtual environments. Therefore, the mobile robot with IC could function solely in familiar environments. To make IC applicable in unfamiliar environments, this study proposes a novel method, instant IC, that eliminates the requirement for a pre-prepared virtual environment. The proposed robot system can instantly generate a virtual environment using actual 360° images of the robot in motion, utilizing instant neural graphics primitives and neural radiance fields. The 360° images allow the entire surrounding environment to be virtualized without requiring specific camera orientations. In addition, by optimizing the density of neural radiance fields using depth estimation results beforehand, the reconstruction accuracy at unknown poses can be guaranteed. Furthermore, we propose a depth scaling method based on the actual measurements obtained by LiDAR to increase the consistency of virtual and real environments. With this instant virtual environment, the proposed system enables teleoperation in unknown environments via the seamless transition between real and virtual environments. The experimental results exhibit consistent and smooth back-and-forth transitions between virtual and real space in mobile robot teleoperation. © 2023 ieee.

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Mitigating Chattering Phenomenon for Photovoltaic system Using Sliding Mode Control Under Rapid Irradiation Level Variation 11

Mitigating Chattering Phenomenon for Photovoltaic System Usi...

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11th ieee international conference on systems and Control, ICSC 2023

作者： Zahra, Bel Hadj Salah Saber, Krim Ali, Hajjaji Mohamed National Engineering School of Monastir University of Monastir Laboratory of Electronic and Microelectronic The Fsm Tunisia National Engineering School of Monastir University of Monastir Laboratory of Automatic Electrical Systems and Environment Tunisia National Engineering School of Monastir University of Monastir Laboratory of Electronic and Micro-electronic Tunisia

ISBN: (纸本)9798350304886

Maximum power point tracking (MPPT) presents an important method for ensuring the optimal operation of photovoltaic systems (PVS). In this paper, we present an MPPT method based on combining the MPPT method: Perturb and Observe (P&O) with the sliding mode controller which is an external voltage controller. To achieve high-performance control, particularly in terms of accuracy and repid response, we propose the integration of derivative and integral terms into the sliding surface. In general, the Sliding Mode Control (smc) consists of two parts: the equivalent and discontinuous control laws. However, the discontinuity related to the discontinuous control law often leads to a chattering phenomenon. To solve this problem, we replace the sign function in the conventional smc method with its sigmoidal approximation. The proposed MPPT method is evaluated under conditions of rapid irradiation changes using the MATLAB/Simulink environment. Furthermore, the proposed method is compared to the P&O MPPT algorithm with a proportional-integral (PI) controller and to the P&O MPPT algorithm with conventional smc. The simulation results of the suggested MPPT approach demonstrate high dynamic performance, particularly in the case of fast variations in irradiance. © 2023 ieee.

关键词： Sliding mode control

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