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International Russian Smart Industry Conference (SmartIndustryCon)

作者： I. I. Naumov R. R. Ibadov D. G. Chebotarev Faculty of Automation Mechatronics and Control Don State Technical University Rostov-on-Don Russia Department of Electrical Engineering and Electronics Don State Technical University Rostov-on-Don Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The flying ad-hoc network (FANET) technology-based secure routing protocol described in this study functions between a ground station and a UAV network. This protocol employs a hybrid authentication technique to guarantee communication dependability. The system is based on an asymmetric method that ensures secure connections between the UAV and the ground control station, as well as between the UAVs themselves. A symmetric scheme with digital signatures is used to encrypt the routing. Before joining the network, the UAV must register. During the registration process, the Key Distribution Center provides the necessary public and private keys for each node that wants to connect. Furthermore, crucial routing data is safeguarded using the TWINE algorithm. Wormhole attacks are avoided by using the packet binding method. Even in the event of an aggressor attack, simulations show that this routing system can sustain effective network functioning, ensuring a high packet delivery ratio and optimal network costs.

关键词： Industries Network topology Authentication Autonomous aerial vehicles Routing Routing protocols Ad hoc networks Safety Registers Grippers

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A Survey on Application of Artificial Intelligence Techniques in Microgrid control

A Survey on Application of Artificial Intelligence Technique...

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Compatibility in Power Electronics (CPE)

作者： Javier Gutiérrez-Escalona Carlos Roncero-Clemente Oleksandr Husev Eva González-Romera María Isabel Milanés-Montero Tomislav Dragičević Electrical Electronic and Control Engineering Department University of Extremadura Badajoz Spain Department of Electrical Power Engineering and Mechatronics Tallin University of Technology Tallin Estonia Wind and Energy Systems Department Technical University of Denmark (DTU) Copenhaguen Denmark

ISBN: (数字)9798350318265

ISBN: (纸本)9798350318272

Concerns over the energy and environmental crisis are driving the strategic integration of distributed generators (DGs) in power systems, hastening the shift to sustainable energy. Microgrids (MGs) emerged as self-reliant, localized power solutions for DGs integration, enhancing grid performance and reliability by allowing grid-connected and islanded modes of operation. Moreover, the dc nature of many DGs and household devices, together with the progress in power electronics, have shifted research from conventional ac MGs towards dc and hybrid ac/dc MGs, which increase the complexity and the number of control scenarios. Therefore, the MG control environment require advanced data-driven algorithms to overcome the stochasticity and non-linear characteristics of MGs systems. In this context, artificial intelligence (AI) techniques demonstrate high potential for enhancing the control and operation in the dynamic MG environment. This paper reviews the most recent research effort regarding the application of AI-based technology in the hierarchical control structure for ac, dc and hybrid ac/dc MG architectures.

关键词： Surveys Reviews Heuristic algorithms Refining Microgrids Propulsion Power electronics

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Self-Tuning Neural Network controller Based on Fuzzy Logic for Multiple Positions Tracking of a Pneumatic Driven Soft Endoscope Actuator

Self-Tuning Neural Network Controller Based on Fuzzy Logic f...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Renzo Acosta Julio Tafur Ruth Canahuire Enginnering Department Control and Automation Engineering Master Degree Program Pontificia Universidad Catolica del Peru Lima Peru Department of Electrical and Mechatronics Engineering Universidad de Ingenieria y Tecnologia - UTEC Lima Peru

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

This paper presents the dynamic modelling and end effector position control of a soft endoscope. Soft endoscope system under study consists mainly of a pneumatic driven soft actuator (PDSA) with four independently chambers. Recurrent neural network (RNN) and dynamic back propagation (DBP) training algorithm are used to obtain PDSA dynamic model. PDSA position controller is based on a feedforward neural network (FNN) and it is trained using PDSA closed loop system (CLS) and DBP training algorithm. CLS stability analysis concludes that it is not possible control PDSA end effector position using one position controller for different end effector initial and desired positions. Fuzzy logic methodology is used to integrate several positions controllers in a one controller valid for all operation range. The controller implementation and close loop system simulation are performed in MATLAB for different end effector desired position to validate system performance in all range of operation.

关键词： Training Fuzzy logic Backpropagation Recurrent neural networks Endoscopes Heuristic algorithms Artificial neural networks

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IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment

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Information Processing in Agriculture 2021年第2期8卷 270-283页

作者： Emmanuel Abiodun Abioye Mohammad Shukri Zainal Abidin Mohd Saiful Azimi Mahmud Salinda Buyamin Muhammad Khairie Idham AbdRahman Abdulrahaman Okino Otuoze Muhammad Shahrul Azwan Ramli Ona Denis Ijike Control and Mechatronics Engineering Department School of Electrical EngineeringUniversiti Teknologi Malaysia(UTM)SkudaiJohorMalaysia Electrical/Electronic Engineering Department Akanu Ibiam Federal PolytechnicUnwanaEbonyi StateNigeria Electrical and Electronics Engineering Department University of IlorinIlorinNigeria Faculty of Science Universiti Putra Malaysia(UPM)Malaysia

The changing dynamics,non-linearity of soil moisture content,as well as other weather and plant variables requires real-time monitoring and accurate predictive model for effective irrigation and crop *** this paper,an improved monitoring and datadriven modelling of the dynamics of parameters affecting the irrigation of mustard leaf plant is *** IoT-based monitoring framework is implemented using ESPresso Lite V2.0 module interfaced with different soil moisture sensors(VH-400),flowmeter(YF-S201)as well as Davis vantage pro 2 weather station to measure soil moisture content,irrigation volume,and computation of the reference evapotranspiration(ETo).The data collected including plant images were transmitted to the Raspberry Pi 3 controller for onward online storage and the data are displayed on the IoT *** combination of both soil moisture and ETo values was used for scheduling a drip irrigated plant grown in a greenhouse for 35 days.A total number of 20,703 experimental data samples are collected from the IoT-based platform was further used for data driven modelling through system identification in *** result shows the development of different predictive models for soil moisture content *** ARX prediction model is found to perform better than the ARMX,BJ and State space model in terms of estimated fit of 91.31%,91.09%,91.08%,and 90.75%***,a robust monitoring framework for irrigation system has been developed,while the performance of the identified ARX model is promising to predict the volumetric soil water content.

关键词： Internet of Things Precision Irrigation System Identification Predictive Model Monitoring control MATLAB

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Gyroball exercise can enhance wrist muscle activation

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International Journal of Industrial Ergonomics 2025年 107卷

作者： Hu, Xinyao Zheng, Jihan Liu, Junshi Mo, Shiwei Jia, Ning Zhao, Zhong Qu, Xingda Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering Shenzhen University China Physical Education Department Dongguan University of Technology China Human Performance Laboratory School of Physical Education Shenzhen University China National Institute of Occupational Health and Poison Control Chinese Center for Disease Control and Prevention China

As a common occupational health concern, wrist injuries not only adversely affect workers’ well-being, but also compromise their productivity. Intermittent short-duration gyroball exercise has the potential to reduce the risk and severity of work-related wrist injuries, however, the underlying biomechanical mechanisms for its effects are still unclear. To address this problem, the present study aimed to examine wrist kinematics and wrist muscle activation with the application of intermittent short-duration gyroball exercise. Eighteen young adults were involved in an experimental study. Comparisons of wrist kinematics and wrist muscle activation were made between the gyroball exercise and two other exercise interventions (i.e., load-holding wrist rotation exercise and free-load wrist rotation exercise). We found that the gyroball exercise intervention was superior to comparative interventions in terms of activating wrist muscles, a critical factor for wrist injury control. This finding implies that intermittent short-duration gyroball exercise could be an effective intervention for preventing and rehabilitating work-related wrist injuries. This quantitative study can provide valuable insights for developing evidence-based guidelines for incorporating gyroball exercise into occupational injury prevention programs. © 2025 Elsevier B.V.

关键词： Industrial hygiene

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KERNEL-BASED LEARNING WITH GUARANTEES FOR MULTI-AGENT APPLICATIONS

arXiv

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arXiv 2024年

作者： Kowalczyk, Krzysztof Wachel, Pawel Rojas, Cristian R. Department of Control Systems and Mechatronics CosmologyWroclaw University of Science and Technology Wroclaw Poland School of Electrical Engineering and Computer Science CosmologyKTH Royal Institute of Technology Stockholm Sweden

This paper addresses a kernel-based learning problem for a network of agents locally observing a latent multidimensional, nonlinear phenomenon in a noisy environment. We propose a learning algorithm that requires only mild a priori knowledge about the phenomenon under investigation and delivers a model with corresponding non-asymptotic high probability error bounds. Both non-asymptotic analysis of the method and numerical simulation results are presented and discussed in the paper. Copyright © 2024, The Authors. All rights reserved.

关键词： Asymptotic analysis

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A K-Means Clustering-Based Optimization of IT2FL for Improved Regenerative Braking Performance 1

A K-Means Clustering-Based Optimization of IT2FL for Improve...

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1st International Conference on Smart mechatronics, ICSMech 2024

作者： Wahid, Muhammad Rizalul Joelianto, Endra Budiman, Bentang Arief Tongroon, Manida Pratama, Mulia Gianti, Mahmudah Salwa Hernadi, Muhammad Fauzan Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Faculty of Mechanical and Aerospace Engineering Bandung Indonesia Kasetsart University Atae Research Unit Department of Mechanical Engineering Sriracha Thailand Pusat Riset Mekatronika Cerdas Organisasi Riset Elektronika dan Informatika-BRIN Bandung Indonesia

ISBN: (纸本)9798350368918

Optimizing regenerative braking systems in electric vehicles presents a complex challenge requiring precise and adaptable control. This research proposes employing K-Means Clustering to the Interval Type-2 Fuzzy Logic (IT2FL) membership functions, thereby improving overall regenerative braking efficiency and enhancing driving range. This research demonstrates that implementing a K-Means in the IT2FL control system in electric vehicles effectively recovers 35.84% of energy. By incorporating a K-means-based approach, the IT2FL controller further enhances vehicle range by 43 kilometers, achieving a total range of 108 kilometers. In comparison, an IT2FL system without K-means recovered only 26.67% of energy and achieved a total range of 93 kilometers. Notably, the IT2FL controller with K-means enabled the electric vehicle to attain an energy efficiency of 22 kilometers per kilowatt-hour. These findings underscore the significant improvement in maximum range offered by the IT2FL controller with K-means compared to alternative methods. © 2024 IEEE.

关键词： Regenerative braking

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Prototype of Turbine Propulsion System with controllable Thrust Vector for Long-Range Unmanned VTOL Aircraft 21st

Prototype of Turbine Propulsion System with Controllable Thr...

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21st Polish control Conference, PCC 2023

作者： Czyba, Roman Lemanowicz, Marcin Domin, Jaroslaw Grzybowski, Jacek Stępień, Izabela Ungier, Lukasz Rosiek, Radoslaw Bialas, Piotr Niemiec, Michal Department of Automatic Control and Robotics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology ul. Akademicka 16 Gliwice44-100 Poland Department of Chemical Engineering and Process Design Faculty of Chemistry Silesian University of Technology ul. Ks. M. Strzody 7 Gliwice44-100 Poland Department of Mechatronics Faculty of Electrical Engineering Silesian University of Technology ul. Akademicka 10a Gliwice44-100 Poland

ISBN: (纸本)9783031351723

The aim of the project was to build a prototype of a turbine drive with a controllable thrust vector for a long-range vertical take-off and landing (VTOL) aircraft. The construction of the prototype required the development of a vectoring system for the tail propulsion system and a dedicated VTOL aircraft stabilization and control system. The prototype of the turbine drive system was based on energy-efficient electric motors. Research also involved modeling the turbine propulsion aerodynamics with usage of computational fluid dynamics (CFD) analysis. As a result of the design stage, a prototype of the propulsion system was created, on which flight tests were carried out. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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A Modified P&O-MPPT Technique Using Fuzzy Logic controller for PV Systems

A Modified P&O-MPPT Technique Using Fuzzy Logic Controller f...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Jabbar, Rafah Ibraheem Mohammed, Karam Khairullah Mekhilef, Saad Mubin, Marizan Seyedmahmoudian, Mehdi Stojcevski, Alex Horan, Ben Becherif, Mohamed Universiti Malaya Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Teknologi Malaysia Control Mechatronics Engineering Department Johor Bahru Malaysia Swinburne University of Technology School of Science Computing and Engineering Technologies HawthornVIC3122 Australia Deakin University School of Engineering GeelongVIC3216 Australia Univ. Bourgogne Franche-Comté UTBM CNRS Rue Ernest Thierry Mieg FEMTO-ST Institute Belfort90000 France

ISBN: (纸本)9798350331790

The perturb and observe (P&O) algorithm is the most popular of the numerous maximum power point tracking (MPPT) algorithms due to its simplicity and ease of implementation. However, the method has limitations regarding convergence speed, steady-state oscillation, and drift problem under sudden irradiance variations. This paper presents an improved P&O-MPPT algorithm to enhance the tracking convergence speed using adaptive duty cycle perturbation step fuzzy logic (FL-D) size. Moreover, a new strategy is added to the algorithm to stop the steady-state oscillation once MPP is tracked. The proposed algorithm was verified using MATLAB/Simulink under constant and varied irradiance levels. The results showed that the proposed algorithm with an adaptive FL-D size could efficiently track an accurate MPP with zero-state oscillation at different irradiance levels. Moreover, the algorithm achieves fast tracking under a rapid change in irradiance. The proposed algorithm was compared with the traditional P&O algorithm and the modified P&O algorithms that have recently been published. The comparison results validated the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Fuzzy logic

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Observer-Based control of Second-Order Multi-vehicle Systems in Bearing-Persistently Exciting Formations

arXiv

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arXiv 2024年

作者： Tang, Zhiqi Fidan, Baris Johansson, Karl H. Mårtensson, Jonas Hamel, Tarek Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden Mechanical and Mechatronics Engineering Department University of Waterloo ON Canada France

This paper proposes an observer-based formation tracking control approach for multi-vehicle systems with second-order motion dynamics, assuming that vehicles' relative or global position and velocity measurements are unavailable. It is assumed that all vehicles are equipped with sensors capable of sensing the bearings relative to neighboring vehicles and only one leader vehicle has access to its global position. Each vehicle estimates its absolute position and velocity using relative bearing measurements and the estimates of neighboring vehicles received over a communication network. A distributed observer-based controller is designed, relying only on bearing and acceleration measurements. This work further explores the concept of the Bearing Persistently Exciting (BPE) formation by proposing new algorithms for bearing-based localization and state estimation of second-order systems in centralized and decentralized manners. It also examines conditions on the desired formation to guarantee the exponential stability of distributed observer-based formation tracking controllers. In support of our theoretical results, some simulation results are presented to illustrate the performance of the proposed observers as well as the observer-based tracking controllers. © 2024, CC BY-NC-ND.

关键词： Acceleration measurement

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