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Cybernetics and Innovations (ICCI), International Conference on

作者： Jirayuth Jantawong Prasongsuk Songsree Warinthorn Kirathihiran Faculty of Engineering and Technology Technology Program in Electrical Technology and Automatic Control System Siam Technology College Bangkok Thailand

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

This paper presents an accurate altitude estimation on a small multirotor UAV. That is crucial for the stability and performance of UAV, particularly in altitude hold control. Barometric pressure sensors are widely used to estimate altitude based on atmospheric pressure, but their readings are highly susceptible to environmental fluctuations, temperature variations, and dynamic airflow effects. To mitigate these altitude errors, this study focuses on enhanced flight control installation techniques, including the physical protection of barometric sensors inside enclosed, well-ventilated compartments to shield them from wind disturbances and rapid pressure changes. The proposed mitigation strategy is validated through ground testing and flight testing, where altitude hold performance is assessed under various environmental conditions. The results confirm that enclosing the barometric sensor within a protective, ventilated chamber significantly reduces altitude estimation errors, leading to more stable altitude hold control with reduced vertical oscillations. These findings highlight the importance of integrated sensor protection in UAV flight control system design and provide a practical framework for improving altitude estimation reliability in both consumer and industrial UAV applications.

关键词： Temperature sensors Wind Technological innovation Fluctuations Autonomous aerial vehicles Barometers Protection Thermal stability Aerospace control Testing

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Toward Using Fuzzy Grey Cognitive Maps in Manned and Autonomous Collision Avoidance at Sea

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IEEE Journal of Oceanic engineering 2025年第2期50卷 1210-1230页

作者： Gil, Mateusz Poczęta, Katarzyna Wróbel, Krzysztof Yang, Zaili Chen, Pengfei Gdynia Maritime University Research Group on Maritime Transportation Risk and Safety Faculty of Navigation Gdynia81-345 Poland Faculty of Electrical Engineering Automatics Control and Computer Science Kielce University of Technology Kielce25-314 Poland Research Institute LiverpoolL3 3AF United Kingdom Wuhan University of Technology School of Navigation Wuhan430063 China Hubei Key Laboratory of Inland Shipping Technology Wuhan430063 China

With Maritime Autonomous Surface Ships (MASS) slowly but steadily nearing full-scale implementation, the question of their safety persists. Regardless of being a disruptive technology, they will likely be subject to the same factors shaping their safety performance as manned ships nowadays are. Yet, the impact of these factors may be different in each case. The current study presents an application of Fuzzy Grey Cognitive Maps (FGCMs) to the comparative evaluation of factors affecting collision avoidance at sea. To this end, subject matter experts have been elicited, and the data obtained from them have been analyzed, concerning how changes in the intensity of given factors would affect safety performance. The obtained results showed that with the use of FGCM, it was possible to model the relative impact of selected factors both on a specific phase of the maritime collision avoidance process as well as on its entirety. The conducted analysis shows noticeable variability of the influence of some factors, depending on the timing of their activation during the process (time dependence), and using FGCM, it was possible to assess its quantification. Furthermore, the results indicate that greater differences can be found between the factors’ impact on phases of an encounter than between manned and autonomous ships. The outcome of this study may be found interesting for all parties involved in maritime safety modeling as well as working on the forthcoming introduction of autonomous ships. © 1976-2012 IEEE.

关键词： Fuzzy Cognitive Maps

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Adaptive Genetic Algorithm Based LQR for Optimal control of Nonlinear Double Pendulum Gantry Crane 1st

Adaptive Genetic Algorithm Based LQR for Optimal Control of...

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Elhabib, Mohamed O. Wahid, Herman Mohamed, Zaharuddin Shutari, Hussein Control and Mechatronics Engineering Division Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru81310 Malaysia School of Electrical and Electronic Engineering Universiti Sains Malaysia Penang Nibong Tebal14300 Malaysia

ISBN: (纸本)9789819646128

Gantry cranes are widely employed to handle heavy loads in construction projects and critical industries such as petrochemical and nuclear power stations. Achieving precise trolley positioning and minimizing sway oscillations are crucial for ensuring safety and operational efficiency. This paper presents an optimal control strategy based on a Linear Quadratic Regulator (LQR), where controller performance is highly sensitive to the selection of its weighting matrices, Q and R. Determining these matrices is often a challenging and time-consuming task. To address this issue, an Adaptive Genetic Algorithm (AGA) is applied to automatically compute the LQR parameters for a nonlinear double pendulum crane model implemented in MATLAB. Simulation results reveal that the proposed AGA-based LQR controller outperforms a conventional LQR tuned with a standard Genetic Algorithm (GA), delivering robust performance across a range of payload masses. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimal control systems

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Reactive Navigation of the Ackermann Steering Robot in Unknown Environments

Reactive Navigation of the Ackermann Steering Robot in Unkno...

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International Conference on Autonomous Robots and Agents, ICARA

作者： ANA ŠELEK IVAN HRABAR SAŠA ŠTEKOVIĆ Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Autegra D.O.O. Zagreb Croatia

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Mobile robots are now widely used in numerous real-world applications that have complex navigation requirements, especially in environments used by humans. This requires highly accurate navigation that can be performed in realtime. In this paper, a method for generating a smooth motion of nonholonomic mobile robots is proposed. It enables robots to move optimally toward the desired goal and allows fast path replanning when encountering unknown or dynamic obstacles. The method generates smooth, collision-free trajectories based on clothoids, ensuring high computational efficiency and suitability for realtime path planning. By applying a smoothing algorithm, the proposed method improves the robot's efficiency in terms of travel time and trajectory length from start to goal, as demonstrated by a comparison with model predictive control.

关键词： Smoothing methods Navigation Dynamics Real-time systems Trajectory Computational efficiency Mobile robots Collision avoidance Testing Predictive control

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An online self-organizing radial basis function neural network based on Gaussian Membership

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Applied Intelligence 2025年第6期55卷 1-17页

作者： Jia, Lijie Li, Wenjing Qiao, Junfei Zhang, Xinliang School of Electrical Engineering and Automation Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment Henan Polytechnic University Jiaozuo454003 China Faculty of Information Technology Beijing University of Technology No. 100 Pingleyuan Chaoyang District Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System No. 100 Pingleyuan Chaoyang District Beijing100124 China

Radial basis function neural network (RBFNN) is one of the most popular neural networks, and an appropriate selection of its structure and learning algorithms is crucial for its performance. Aiming to alleviate the sensitivity of the RBFNN to its parameters and improve the overall performance of the network, this study proposes a Gaussian Membership-based online self-organizing RBF neural network (GM-OSRBFNN). First, the Gaussian Membership is introduced to enhance network insensitivity to network parameters and used as a similarity metric to indicate the similarity between the sample to a hidden neuron and that between hidden neurons. Second, the similarity metric is used to design the neuron addition and merging rules to achieve a self-organizing network structure, and error constraints are introduced to the neuron addition rule;also, the noisy neuron deletion rule is defined to make the network structure more compact. In addition, an online fixed mini-batch gradient algorithm is used for online learning of network parameters, which can guarantee fast and stable convergence of the network. Finally, the proposed GM-OSRBFNN is tested on common nonlinear system modeling problems to verify its effectiveness. The experimental results show that compared to the existing models, the GM-OSRBFNN can achieve competitive prediction performance with a more compact network structure, faster convergence speed, and, more importantly, better insensitivity to network parameters. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Radial basis function networks

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BAT Optimized SMC for Continuous Stirred Tank Reactor

BAT Optimized SMC for Continuous Stirred Tank Reactor

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IEEE Information Technology and Mechatronics engineering Conference (ITOEC)

作者： Husam E. Elfadel Haroon Congzhi Huang School of Control and Computer Engineering North China Electric Power University Beijing China Department of Electrical and Electronic Engineering Faculty of Engineering Omdurman Islamic University Khartoum Sudan

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

This topic proposed a Sliding Mode control (SMC) strategy utilizing the BAT Algorithm (BAT-SMC) for regulating concentration and temperature in a Continuous Stirred Tank Reactor (CSTR) system. The SMC is designed to maintain concentration (CA) and temperature (T) within desired setpoints by adapting sliding surfaces in the presence of disturbances and system uncertainties. The BAT Algorithm enhances the SMC by optimizing control parameters, reducing chattering effects, and improving tracking accuracy. Simulations validate the efficacy of BAT-SMC, showing improved dynamic performance for both concentration and temperature control compared to other controllers.

关键词： Uncertainty Mechatronics Heuristic algorithms Optimal control Coolants Temperature control Continuous-stirred tank reactor Feeds Information technology Sliding mode control

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Semantic Communication based on Generative AI: A New Approach to Image Compression and Edge Optimization

arXiv

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arXiv 2025年

作者： Pezone, Francesco Barbarossa, Sergio Caire, Giuseppe Di Lorenzo, Paolo Kountouris, Marios Bennis, Mehdi Sapienza University of Rome Department of Computer Control and Management Engineering Italy Technische Universität Berlin Faculty 4 - Electrical Engineering and Computer Science Germany

As digital technologies continue to advance, modern communication networks face unprecedented challenges in handling the vast amounts of data produced daily by connected intelligent devices. Autonomous vehicles, smart sensors, IoT systems etc., are gaining more and more interest and new communication paradigms are needed. This thesis addresses these challenges by combining semantic communication with generative models to optimize image compression and resource allocation in edge networks. Unlike traditional bit-centric communication systems, semantic communication prioritizes the transmission of meaningful data specifically selected to convey the meaning rather than obtain a faithful representation of the original data. The communication infrastructure can benefit of the focus solely on the relevant parts of the data due to significant improvements in bandwidth efficiency and latency reduction. Central to this work is the design of semantic-preserving image compression algorithms, utilizing advanced generative models such as Generative Adversarial Networks and Denoising Diffusion Probabilistic Models. These algorithms compress images by encoding only semantically relevant features and exploiting the generative power at the receiver side. This allows for the accurate reconstruction of high-quality images with minimal data transmission. The thesis also introduces a Goal-Oriented edge network optimization framework based on the Information Bottleneck problem and stochastic optimization, ensuring that communication resources are dynamically allocated to maximize efficiency and task performance. By integrating semantic communication into edge networks, the proposed system achieves a balance between computational efficiency and communication effectiveness, making it particularly suited for real-time applications. The thesis compares the performance of these semantic communication models with conventional image compression techniques, using both classical and semantic-awar

关键词： Image compression

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A Three-Phase Totem-Pole AC-DC Converter Based Off-Board Charger for Electric Vehicles

A Three-Phase Totem-Pole AC-DC Converter Based Off-Board Cha...

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International Youth Conference on Radio Electronics, electrical and Power engineering (REEPE)

作者： Tony Mamdouh Ibrahim Abdelsalam Mostafa I. Marei Electrical and Control Engineering Dep. College of Engineering & Technology. Arab Academy for Science Technology & Maritime Transport Cairo Egypt Electrical Power and Machines Department Faculty of Engineering Ain Shams University Cairo Egypt

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

This paper presents the design, implementation, and performance evaluation of a three-phase bridgeless totem-pole off-board charger specifically developed for electric vehicles (EVs). The charger is characterized by a modular architecture that allows for scalability, consisting of three single-phase parallel bridgeless totem-pole AC-DC converters, each capable of supplying one-third of the total rated power. The control system of the charger employs three cascaded control loops to ensure stable operation and facilitate a seamless transition from current control mode to voltage control mode throughout the battery charging process, accommodating a wide range of EV battery configurations. Furthermore, the charger is engineered to support and improve grid power quality, ensuring a sinusoidal grid current waveform and unity power factor, thereby enhancing efficient power transfer while minimizing grid disturbances. The performance of this level ‘3’ charger was assessed and validated through MATLAB/Simulink simulations, with testing conducted on battery bank voltages of 400V, 800V, and lOOOV for three electric vehicles.

关键词： Reactive power Scalability Power quality Process control Electric vehicles Batteries MATLAB Voltage control Vehicle dynamics Testing

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Three-factor assessment of rutting factor of modified asphalt binders and mastics in the ageing process

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Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第3期73卷

作者： Mielczarek, Marta Andrzejczak, Karol Slowik, Mieczyslaw Poznan University of Technology Faculty of Civil and Transport Engineering Institute of Civil Engineering Piotrowo 5 Poznań60-965 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Mathematics Piotrowo 3A Poznań60-965 Poland

This paper discusses the research and multivariate analyses of the rheological properties of asphalt binders and mastics containing various mineral fillers and SBS copolymer-modified bitumen. In the experimental design employed, three types of mineral filler were used: limestone, basalt, or granodiorite. To determine the effect of ageing processes on the rheological properties of the obtained mastics, all asphalt binders tested were subjected to short-term (technological) ageing simulated under laboratory conditions using the RTFOT method. The main aim of this study was to evaluate the rutting resistance of modified binders and asphalt mastics depending on such factors as: the type of mineral filler, the percentage of SBS copolymer, temperature, and the influence of the ageing process. A three-way ANOVA was used to test for rutting resistance. The results of laboratory tests and statistical analyses made it possible to assess the significance of the factors examined in the research on the rutting resistance of asphalt binders and mastics, both before and after short-term ageing. © 2025 The Author(s).

关键词： Analysis of variance (ANOVA)

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Research on the Failure Mechanism and Fault Prediction Method of High Voltage DC Relays

Research on the Failure Mechanism and Fault Prediction Metho...

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electrical Automation and Artificial Intelligence (ICEAAI), International Conference on

作者： XiIi Wang Xu Chang Shijun Gai Yanying Shi Faculty of Electrical and Control Engineering Liaoning Technical University Huludao Liaoning China PetroChina Jinxi Petrochemical Company Huludao Liaoning China

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

As an important switching component, studying the fault prediction model of high-voltage direct current relays is of great significance for improving the power supply safety in the field of new energy. With the goal of analyzing the failure mechanism of high-voltage direct current relays and predicting their faults, a high-voltage direct current relay experimental system was built, and a large number of on-off experiments were conducted on multiple relays. BP and PSO-BP neural network prediction models were constructed using MATLAB, and arc energy was selected as the input feature quantity for the prediction model. The accuracy of the prediction model was evaluated using R2, MAE, MSE, and the results showed that the PSO- BP neural network prediction model is more suitable for fault prediction of high-voltage DC relays.

关键词： Accuracy Welding Neural networks Failure analysis High-voltage techniques Switches Predictive models Mathematical models Data models Relays

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