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IEEE Southeastcon

作者： Kyle Odoy Erick J. Rodríguez-Seda Department of Weapons Robotics and Control Engineering United States Naval Academy Annapolis MD

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Multi-agent coverage control refers to the task of coordinating autonomous robots to effectively survey and gather information across a task-domain. This paper introduces a novel approach that addresses agents equipped with anisotropic sensors and constrained by nonholonomic movement, aiming to ensure persistent coverage and maintain awareness over a large-scale domain. The approach employs redefined Voronoi partitions that leverage each agent's local coverage domain based on its relative task load. The task load herein refers to the level of awareness that each agent has about the domain and the size of its area of dominance, all indirectly encoded in the Voronoi's mass. To account for the vehicles' nonholonomic nature and velocity constraints, the proposed approach is extended using the minimum curvature-based distance when determining the agent's area of dominance. A set of simulations involving teams of three and five agents showcases the effectiveness of the proposed control approach.

关键词： Surveys Anisotropic control systems Sensor systems Sensors Multi-agent systems Load modeling Autonomous robots

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Experimental Investigation of a Semi-Autonomous Search and Rescue System

Experimental Investigation of a Semi-Autonomous Search and R...

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UKACC International Conference on control (control)

作者： Richard T. O'Brien Eli Walz Katherine R. Hammonds Megan Rumbaugh Robotics and Control Engineering Department United States Naval Academy Annapolis MD

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

A previously-proposed semi-autonomous search and rescue system is investigated experimentally. A stationary vision system identifies and tracks a victim using an object detection neural network. The vision system then guides an autonomous unmanned ground vehicle to the victim's location using a ROS 2 publisher-subscriber communication protocol. A series of experiments are conducted with off-the-shelf components to investigate the impact of several design parameters. The resulting experimental data demonstrates that a fast and accurate response can be achieved. Furthermore, guidelines are established for parameter selection in future experiments.

关键词： Protocols Robot vision systems Neural networks Object detection Cameras Land vehicles Delays

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FPGA Implementation of Neural Network Accelerator for PCB Defect Detection 3

FPGA Implementation of Neural Network Accelerator for PCB De...

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3rd International Symposium on Computer engineering and Intelligent Communications, ISCEIC 2022

作者： Zhang, Jinzhou Zhang, Hui Zhao, Bingrui Liu, Jiaxuan Zhou, Xidong College of Electrical and Information Engineering Changsha University of Science & Technology Changsha China School of Robotics Hunan University Changsha China Department of Control Science and Engineering Hunan University Changsha China

ISBN: (纸本)9781510660298

With the rapid development of artificial intelligence, deep neural network (DNN) has been widely used in industrial defect detection, intelligent driving, medical research, etc. However, DNN is still limited in the implementation of edge computing and mobile devices due to its characteristics of high model complexity and high computing resource consumption. Therefore, we designed a neural network hardware accelerator based on Field Programmable Gate Array (FPGA) for printed circuit board (PCB) defect detection. In this paper, firstly, since structure re-parameterization can improve the network's accuracy without increasing the inference model's complexity, we introduce structure reparameterization to improve the YOLOv2 model and propose RepYOLOv2. Secondly, a low-bit quantization method based on integer type is adopted to quantify the model data to 6-bit. Then a specific convolutional computing module and neural network hardware accelerator are designed according to the characteristics of the model. Experimental results on Xilinx ZCU102 FPGA show that the real-time processing speed of the system reaches 2.12 FPS, the throughput is 68.53 GOP/s, and the power consumption is only 1.12 W. Compared with similar work, better performance is obtained. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.

关键词： Deep neural networks

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Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion

Novel Disturbance Observer Relevant Parametric System Identi...

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2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Jung, Hanul Tacx, Paul Oomen, Tom Oh, Sehoon Dgist Department of Robotics Engineering Daegu42988 Korea Republic of Eindhoven University of Technology Control Systems Technology Group Department of Mechanical Engineering P.O. Box 513 Eindhoven5600 MB Netherlands

ISBN: (纸本)9798350335446

In this paper, novel parametric identification is addressed by the disturbance observer (DOB) relevant algorithm. To fully utilize the disturbance observer, a proper nominal model, which is a parametric model, is essential. The control performance of the DOB can be checked based on the robust stability criterion, which is related to the modeling error and the desired bandwidth of the DOB. Consequently, it is beneficial to evaluate the parametric model in the system identification procedure. Therefore, this paper proposes a novel disturbance observer-relevant system identification algorithm based on the robust stability criterion of the disturbance observer. The effectiveness of the proposed method is validated by showing the numerical simulations under specific conditions. © 2023 IEEE.

关键词： Stability criteria

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TinyML Speech Classification Embedded Ai Module for Hand Rehabilitation Device 3

TinyML Speech Classification Embedded Ai Module for Hand Reh...

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3rd International Conference on Mechatronics, control and robotics, ICMCR 2025

作者： Numsomran, Arkorn Numsomran, Arjin Chaoraingern, Jutarut Triam Udom Suksa Pattanakarn Suvarnabhumi School Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Robotics and AI Engineering Bangkok Thailand

ISBN: (纸本)9798331544546

Recent advancements in artificial intelligence and machine learning have significantly improved healthcare, especially in the development of assistive technologies for rehabilitation. This paper introduces a method for hand rehabilitation that utilizes the capabilities of tiny machine learning to enhance speech classification in a rehabilitation device. The proposed method employs a CNN model capable of classifying speech signals that are indicative of different hand movement patterns. Patients emit these speech signals during prescribed hand exercises, which are crucial for their rehabilitation process. The main focus of this study is on training and deploying a speech classification system that can work in the resource-limited environment of TinyML platforms. We detail the process of capturing speech data, preprocessing it, and extracting the most features relevant to different hand movements. Our results show that using TinyML to help with hand rehabilitation works. The method we came up with shows how TinyML could change the way rehabilitative devices are controlled, and it also shows us what personalized and easy-to-use rehabilitation tools might look like in the future. © 2025 IEEE.

关键词： Human rehabilitation equipment

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DESKO: STABILITY-ASSURED ROBUST control OF NONLINEAR SYSTEMS WITH A DEEP STOCHASTIC KOOPMAN OPERATOR 10

DESKO: STABILITY-ASSURED ROBUST CONTROL OF NONLINEAR SYSTEMS...

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10th International Conference on Learning Representations, ICLR 2022

作者： Han, Minghao Euler-Rolle, Jacob Katzschmann, Robert K. Department of Control Science and Engineering Harbin Institute of Technology China Soft Robotics Lab ETH Zurich Switzerland

The Koopman operator theory linearly describes nonlinear dynamical systems in a high-dimensional functional space and it allows to apply linear control methods to highly nonlinear systems. However, the Koopman operator does not account for any uncertainty in dynamical systems, causing it to perform poorly in real-world applications. Therefore, we propose a deep stochastic Koopman operator (DeSKO) model in a robust learning control framework to guarantee stability of nonlinear stochastic systems. The DeSKO model captures a dynamical system's uncertainty by inferring a distribution of observables. We use the inferred distribution to design a robust, stabilizing closed-loop controller for a dynamical system. Modeling and control experiments on several advanced control benchmarks show that our framework is more robust and scalable than state-of-the-art deep Koopman operators and reinforcement learning methods. Tested control benchmarks include a soft robotic arm, a legged robot, and a biological gene regulatory network. We also demonstrate that this robust control method resists previously unseen uncertainties, such as external disturbances, with a magnitude of up to five times the maximum control input. Our approach opens up new possibilities in learning control for high-dimensional nonlinear systems while robustly managing internal or external uncertainty. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

关键词： Dynamical systems

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Model Predictive Torque control of Six-Phase Switched Reluctance Motors Based on Improved Voltage Vector Strategy

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7650-7661页

作者： Yang, Yifei Sun, Xiaodong Dianov, Anton Demidova, Galina Prakht, Vladimir Wang, Yong Han, Shouyi Suzhou Vocational University School of Mechanical and Electrical Engineering Suzhou215104 China Jiangsu University Automotive Engineering Research Institute Zhenjiang212013 China Wenzhou University Pingyang Institute of Intelligent Manufacturing Wenzhou325035 China ITMO University Faculty of Control Systems and Robotics Saint Petersburg197101 Russia Ural Federal University Department of Electrical Engineering Yekaterinburg620062 Russia Jiangsu University School of Electrical and Information Engineering Zhenjiang212013 China

To rapidly and accurately establish the model of switched reluctance motors (SRMs) and enhance torque control performance, this article proposes a model predictive torque control (MPTC) strategy based on the optimized voltage vector. First, a fourth-order Fourier series is used to calculate the flux and torque models, and a complete nonlinear model of the SRM is constructed using the Kriging model. Second, the torque characteristics are used to divide the sectors, thereby reducing the number of candidate voltage vectors (CVVs) and effectively decreasing the computational burden of predictive control. Finally, an adaptive adjustment algorithm for the sector boundary angle is proposed, where the position of the sectors is determined based on variations in speed and load. The proposed method reduces torque ripple and enhances dynamic response capability. The effectiveness of this approach is validated through experiments on a 12/10 pole six-phase SRM prototype. © 2015 IEEE.

关键词： Vectors

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Combined Filters Design, Using the Principle of Internal Models

Combined Filters Design, Using the Principle of Internal Mod...

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2024 International Russian Automation Conference, RusAutoCon 2024

作者： Gaiduk, Anatoly Denisenko, Darya Prokopenko, Nikolay Southern Federal University Scientific Design Office Robotics and Control Systems Department of Automatic Control Systems Rostov-on-Don Taganrog Russia Department of scientific research Don State Technical University Rostov-on-Don Russia Department of Automatic Control Systems Southern Federal University Rostov-on-Don Russia Don State Technical University Department of Information Systems and Radio Engineering Rostov-on-Don Russia

To design active analog, discrete-analog and digital filters a new method is suggested, taking into account the conditions of selective invariance and using the internal models principle of the dynamic systems. For this purpose, the structure of each basic filter ensures the presence of an explicit spectral model of the filtered signal. Such a filter is selectively invariant, and this property depend only on the spectrum-setting parameters and do not depend on other parameters. It is suggest-ed to carry out the design of the combined selective filters by integration of the suggested basic second-order filters, focusing on the log magnitude plot of the latter. This makes possible to minimize the order of the combined both analog and digital filters. The combined selective filters are distinguished by high stability of selective properties and can be used in the systems for measurement, signal processing, data transmission, as well as automatic and automated control of various social, production and special facilities. © 2024 IEEE.

关键词： Wiener filtering

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LMI-Based Luenberger Observer Design for Uncertain Nonlinear Systems with External Disturbances and Time-Delays

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IEEE Access 2023年 11卷 71823-71839页

作者： Karami, Hamede Nguyen, Ngoc Phi Ghadiri, Hamid Mobayen, Saleh Bayat, Farhad Skruch, Pawel Mostafavi, Fatemeh University of Zanjan Faculty of Engineering Department of Electrical Engineering Zanjan45371-38791 Iran Sejong University Department of Aerospace Engineering Seoul05006 Korea Republic of Islamic Azad University Qazvin Branch Department of Electrical Engineering Qazvin34199-15195 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliou640301 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper investigates the simultaneous design of a controller and Luenberger state observer for systems with time-delays, external disturbances, uncertainties, modeling errors, and unknown nonlinear perturbations. The state-feedback control approach and state-observer existence conditions are formulated using the Linear Matrix Inequalities (LMIs). By defining the estimation error, the equations of the closed-loop system are rewritten. External disturbances, uncertainties, unknown nonlinear perturbations, and constant time-delays are considered in system modeling. By using LMI techniques, the estimation error is converged to zero. Therefore, the time-delays, uncertainties, and external disturbance effects on the system output, which have not been considered simultaneously before, are minimized, and the closed-loop system is stabilized. The performance of the proposed approach is verified by simulation of two examples, Flexible-Link Manipulator (FLM) dynamics, and Continuous Stirred Tank Reactor (CSTR) system. These examples illustrate the reliability of the suggested method. © 2013 IEEE.

关键词： Linear matrix inequalities

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Light Scattering Experiments and Simulations from Laser Beams with Orbital Angular Momentum

Light Scattering Experiments and Simulations from Laser Beam...

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2024 Applications of Lasers for Sensing and Free Space Communications, LS and C 2024

作者： Sivaprakasam, Vasanthi Hart, Matthew Divitt, Shawn Xavier, Marquise O’Malley, Owen Avramov, Svetlana U.S. Naval Research Laboratory 4555 Overlook Ave SW WashingtonDC20375 United States Weapons Robotics and Control Engineering Department United States Naval Academy United States

The angular elastic scattering signal intensity is simulated and measured from suspended single particles for varying order mode, orbital angular momentum laser beams. Comparison between simulation/experiment and to s... 详细信息

关键词： Laser beams

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