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Intelligent control, Computing and Communications (IC3), International Conference on

作者： Jackson J. Justo Galina Demidova Dmitry Lukichev Nikolai Poliakov Peter Makolo Ramesh C. Bansal Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Department of Electrical Engineering University of Dar es Salaam Dar es Salaam Tanzania Depatment of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electric Electronic and Computer Engineering University of Pretoria Pretoria South Africa

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

During the last two decades, interest in grid integrated renewable energy sources (RERs) into the electrical power grids has significantly grown. The motive being a promising strategy to reduce greenhouse gas emissions generated by conventional power plants (CPPs) and hence environmental consequences, decrease losses in distribution lines to improve power system supply efficiency and reliability to consumers. As a result, several CPPs are being replaced by RERs such as solar PV system, wind energy, micro hydro-turbine, fuel cell, and small gas power plants. These are installed close to customers on low-voltage and medium-voltage sites to reduce losses in the network and improve power quality, overall efficiency and reliability. However, grid-connected RERs via inverter decreases system inertia due to decrease in CPPs with rotating mass serving as an immediate natural response to frequency deviations following network disturbances. Therefore, this paper presents the design of dynamic virtual-inertia control (DVIC) scheme. The developed DVIC incorporates the mechanism to adjust active and reactive demand in response to any frequency and voltage variations to ensure system stability. To validate the suitability of the presented technique, MATLAB/Simulink model is developed and simulated under various operating scenarios. Using the results obtained simulation study, it is evidently the proposed DVIC shows improved performance is achieved than when no inertia control system applied.

关键词： Time-frequency analysis Renewable energy sources Power system dynamics Microgrids Power system stability Inverters Power system reliability Reliability Frequency control Power generation

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Adaptive observer for a nonlinear system with partially unknown state matrix and delayed measurements

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IFAC-PapersOnLine 2023年第2期56卷 8702-8707页

作者： Olga Kozachek Alexey Bobtsov Nikolay Nikolaev Department of Control Systems and Robotics ITMO University Kronverkskiy av. 49 Saint-Petersburg 197101 Russia Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia

Problem of an adaptive state observer design for nonlinear system with unknown time-varying parameters and under condition of delayed measurements is considered. State observation problem was raised by many researchers (see for example Sanx et al. (2019)). In this paper the results proposed in Bobtsov et al. (2021b), Bobtsov et al. (2021a), Bobtsov et al. (2022a), Bobtsov et al. (2022b) are developed. The problem is solved under assumption that the state matrix can be represented as sum of known and unknown parts. The output vector is measured with a known constant delay. An adaptive observer which reconstructs unmeasured state and unknown time-varying parameter is proposed.

关键词： nonlinear system delay adaptive observer parameter identification

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Adaptive Block Elevation Mapping for Large-scale Scene

Adaptive Block Elevation Mapping for Large-scale Scene

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhou, Yang Zhu, Shiqiang Huang, Huang Li, Yuehua Gu, Jason The Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China The Beijing Institute of Control Engineering Beijing100094 China The Beijing Research Institute Zhejiang Laboratory Beijing100094 China The Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

Dense map that contains the surrounding geometry and vision information of a robot is widely used for path planning, navigation, obstacle avoidance and other applications. Considering the performance of the processing unit mounted on the robot is limited, mapping algorithm has to make compromise by sacrificing speed and precision. It will be more challenging when the dense mapping scene is very large because the memory consumption will be greatly increased and the map is difficult to be extended if beyonding the initial map. To suppress the negative impact from the increased map scale, we proposed a novel block mapping approach to generate the dense map in large scale of scene. In this work, the elevation map is selected as the base dense map. The entire elevation map is segmented into numerous block maps of which size is much smaller than that of the entire map. The present moment of lidar and vision measurements are used to generate the local elevation map. The local elevation map is used to update block maps which are adaptively generated along the motion trajectory. A memory-disk interaction mechanism, which the block maps will be loaded to memory or saved to local disk when needed, is introduced. Our block mapping approach is tested on the KITTI datasets, and the results demonstrate that the mapping approach can stably operate in a large scale of scene with a much smaller consumption of memory. © 2022 IEEE.

关键词： Motion planning

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Model for Wind-Related Phenomena Estimation Using Polarization Characteristics of Microwave Radar Signal 16

Model for Wind-Related Phenomena Estimation Using Polarizati...

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16th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer engineering, TCSET 2022

作者： Averyanova, Yuliya Yanovsky, Felix Shcherbina, Olga Ostroumov, Ivan Kuzmenko, Nataliia Zaliskyi, Maksym Solomentsev, Oleksandr Sushchenko, Olha National Aviation University Air Navigation Systems Department Kyiv Ukraine National Aviation University Electronics Robotics Monitoring and IoT Technologies Department Kyiv Ukraine National Aviation University Telecommunication and Radio Engineering Systems Department Kyiv Ukraine National Aviation University Aerospace Control Systems Department Kyiv Ukraine

ISBN: (纸本)9781665468619

Radar Polarimetry is a convenient and promising technique to obtain information about target scattering properties. In this paper, the hydrometeor shape and orientation variations under the dynamic phenomena influence are analyzed to connect polarization radar measurements with atmospheric dynamic processes. The new model to state regularities and to put the interconnections between atmospheric dynamics and polarization characteristics of the reflected radar signal is developed. The model is based on an analysis of two regimes of drop deformation under the wind influence. The first is the regime of subcritical deformation and the second is the regime of critical deformation that leads to the drop's shatter. The developed new model demonstrates the possibility to use polarimetry for estimation of wind and wind-related phenomena and can be used to improve drop size distribution estimate, rainfall intensity estimates as well. © 2022 IEEE.

关键词： Meteorological radar

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SDA-SNE: Spatial Discontinuity-Aware Surface Normal Estimation via Multi-Directional Dynamic Programming

SDA-SNE: Spatial Discontinuity-Aware Surface Normal Estimati...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Nan Ming Yi Feng Rui Fan Department of Control Science & Engineering MIAS Group Robotics & Artificial Intelligence Laboratory Tongji University Shanghai China

ISBN: (纸本)9781665456715

The state-of-the-art (SoTA) surface normal estimators (SNEs) generally translate depth images into surface normal maps in an end-to-end fashion. Although such SNEs have greatly minimized the trade-off between efficiency and accuracy, their performance on spatial discontinuities, e.g., edges and ridges, is still unsatisfactory. To address this issue, this paper first introduces a novel multi-directional dynamic programming strategy to adaptively determine inliers (co-planar 3D points) by minimizing a (path) smoothness energy. The depth gradients can then be refined iteratively using a novel recursive polynomial interpolation algorithm, which helps yield more reasonable surface normals. Our introduced spatial discontinuity-aware (SDA) depth gradient refinement strategy is compatible with any depth-to-normal SNEs. Our proposed SDA-SNE achieves much greater performance than all other SoTA approaches, especially near/on spatial discontinuities. We further evaluate the performance of SDA-SNE with respect to different iterations, and the results suggest that it converges fast after only a few iterations. This ensures its high efficiency in various robotics and computer vision applications requiring real-time performance. Additional experiments on the datasets with different extents of random noise further validate our SDA-SNE's robustness and environmental adaptability. Our source code, demo video, and supplementary material are publicly available at ***/SDA-SNE.

关键词： Surface cleaning Interpolation Computer vision Three-dimensional displays Heuristic algorithms Estimation Streaming media

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Path Tracking for Wheeled Mobile Robot Using Non Linear Model Predictive control in Indoor Environment

Path Tracking for Wheeled Mobile Robot Using Non Linear Mode...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Alessandro Bozzi Simone Graffione Michiel M.W. Kockelkoren Roberto Sacile Enrico Zero Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) University of Genoa Genoa Italy Delft Center for Systems and Control (DCSC) Delft University of Technology Delft Netherlands

Wheeled Mobile Robots (WMR) with the assistance of Information Communication Technology (ICT) can navigate and perform some tasks in an uncontrolled environment. They can experience some problems in task management if they can not localize themself in indoor/outdoor environments. Different algorithms can be exploited to evaluate the proper control law to track a default path. In this paper, a path-tracking algorithm for a WMR has been tested for an indoor environment, with a delimited area spanned by localization tags. The WMR must check some waypoints during its path until the last one, where the WMR re-start the simulation. In this work, the control law applied for the experiments is the Non-Linear Model Predictive controller (NMPC). The control algorithm is tested using two experiments, the first one is based on the robot movements in a simulation environment using the Gazebo tools, and the second one is related to a real context where the mobile robot moves in an indoor environment.

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A New Agile Actuation System of a Cable-Driven Parallel Robot

A New Agile Actuation System of a Cable-Driven Parallel Robo...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian MohammadJavad Shabani SeyedSina Seyedi HasanAbadi Mohammadreza Dahaaghin Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotic and Automated Systems (ARAS) K. N. Toosi University of Technology Tehran Iran

Cable-driven Parallel Robots (CDPRs) offer a wider range of workspace compared to rigid-link parallel robots. These robots are equipped with an actuation system that satisfies some requirements, such as having low inertia and a negligible amount of friction. These two criteria lead to the agility definition of a system. On the other hand, winch-drum actuation systems should be able to wind the cable properly, in a way it does not be wound on itself. In this paper, an innovative winch-drum actuation system with a universal joint module is designed and fabricated for a CDPR. The winch-drum module is equipped with a power screw module which allows the cable to be wound properly around the drum and the universal joint module allows the cable to accordingly orient within the workspace. To validate the proposed designated system, it is experimentally evaluated in two control scenarios; i.e. reaching a set point and path tracking task The results show that the proposed actuation system fulfills the desired criteria and has the potential to be implemented in any other CDPR.

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A robust energy flow predictor based on CNN-LSTM for prosumer-oriented microgrids considering changes in biogas generation

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Energy 2025年 326卷

作者： Maślak, Grzegorz Orlowski, Przemyslaw West Pomeranian University of Technology in Szczecin Department of Automatic Control and Robotics Faculty of Electrical Engineering Sikorskiego 37 Szczecin70-313 Poland West Pomeranian University of Technology in Szczecin Doctoral School Piastów 19 Szczecin70-310 Poland

Information, such as reliable demand and generation forecasts is crucial for appropriate energy management in microgrids. However, the most valuable data is the aggregate energy flow in the managed network, rather than its components. The large share of renewable energy in such installations is associated with fluctuations. A promising renewable source that helps counteract them is biogas. However, a source subject to uncertainties which should be taken into account. The work focuses on developing a method for obtaining a CNN-LSTM microgrid energy flow predictor dedicated to energy management systems. The selection of the hyper-parameters of the artificial neural network is formulated as a robust meta-optimisation problem and solved using surrogate optimisation. The solution ensures obtaining a CNN-LSTM network providing the lowest prediction error with the largest change in the share of biogas in the microgrid. Detailed analyses have shown that in addition to obtaining high robustness to biogas, the solution does not lose accuracy while changing the number of prosumers with photovoltaic installations. Beyond meta-optimisation, ranges of certain hyper-parameters providing adequate prediction quality for all analysed prediction horizons are identified. © 2025 Elsevier Ltd

关键词： Information management

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Enhancing Precision Agriculture Through Human-in-the-Loop Planning and control

Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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On the Robustness of Adversarial Training Against Uncertainty Attacks

arXiv

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arXiv 2024年

作者： Ledda, Emanuele Scodeller, Giovanni Angioni, Daniele Piras, Giorgio Cinà, Antonio Emanuele Fumera, Giorgio Biggio, Battista Roli, Fabio Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Via Dodecaneso 35 Genova16146 Italy Department of Electric and Electronic Engineering University of Cagliari Via Marengo 3 Cagliari09100 Italy

In learning problems, the noise inherent to the task at hand hinders the possibility to infer without a certain degree of uncertainty. Quantifying this uncertainty, regardless of its wide use, assumes high relevance for security-sensitive applications. Within these scenarios, it becomes fundamental to guarantee good (i.e., trustworthy) uncertainty measures, which downstream modules can securely employ to drive the final decision-making process. However, an attacker may be interested in forcing the system to produce either (i) highly uncertain outputs jeopardizing the system’s availability or (ii) low uncertainty estimates, making the system accept uncertain samples that would instead require a careful inspection (e.g., human intervention). Therefore, it becomes fundamental to understand how to obtain robust uncertainty estimates against these kinds of attacks. In this work, we reveal both empirically and theoretically that defending against adversarial examples, i.e., carefully perturbed samples that cause misclassification, additionally guarantees a more secure, trustworthy uncertainty estimate under common attack scenarios without the need for an ad-hoc defense strategy. To support our claims, we evaluate multiple adversarial-robust models from the publicly available benchmark RobustBench on the CIFAR-10 and ImageNet datasets. © 2024, CC BY.

关键词： Adversarial machine learning

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