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1st AIRPHARO Workshop on Aerial Robotic systems Physically Interacting with the Environment, AIRPHARO 2021

作者： Konyalioglu, Turan Alnipak, Sinan Altug, Erdinc İstanbul Technical University System Dynamics and Control Graduate Program İstanbul Technical University Autonomous Systems Research Laboratory Department of Mechanical Engineering İstanbul Turkey

ISBN: (纸本)9781665433891

Within the last decade, e-commerce has increased at an extraordinary level. The widespread use of Unmanned Aerial Vehicles (VAVs) in the logistics sector can reduce traffic density, improve delivery time, and can provide contactless delivery. This work proposes a new hybrid VAV, that combines the benefits of vertical take-off and land vehicle and a fixed-wing aircraft. It can carry multiple packages, which can decent automatically towards the recipients. This approach eliminates time-consuming landing maneuvers of the VA V for delivery. This work focuses on the design of the vehicle, and the challenges of the transitions from VTOL to aircraft modes and vice versa with a Model Predictive controller. © 2021 IEEE.

关键词： Fixed wings

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Deep Neural Network Based Optimal control of Greenhouses

arXiv

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arXiv 2023年

作者： Sathyanarayanan, Kiran Kumar Sauerteig, Philipp Streif, Stefan Technische Universität Chemnitz Automatic Control and System Dynamics Lab Chemnitz09126 Germany Fraunhofer Institute for Molecular Biology and Applied Ecology Department of Bioresources Giessen Germany

Automatic control of greenhouse crop production is of great interest owing to the increasing energy and labor costs. In this work, we use two-level control, where the upper level generates suitable reference trajectories for states and control inputs based on day-ahead predictions. These references are tracked in the lower level using Nonlinear Model Predictive control (NMPC). In order to apply NMPC, a model of the greenhouse dynamics is essential. However, the complex nature of the underlying model including discontinuities and nonlinearities results in intractable computational complexity and long sampling times. As a remedy, we employ NMPC as a data generator to learn the tracking control policy using deep neural networks. Then, the references are tracked using the trained Deep Neural Network (DNN) to reduce the computational burden. The efficiency of our approach under real-time disturbances is demonstrated by means of a simulation study. © 2023, CC BY-NC-ND.

关键词： Deep neural networks

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Design and Wave Propagation Characterization of Starchiral Metamaterials

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Acta Mechanica Solida Sinica 2022年第2期35卷 215-227页

作者： Yajun Xin Han Wang Cong Wang Jinxin Yao Qian Ding Haoqiang Gao Shuliang Cheng Yongtao Sun Key Laboratory of Green Construction and Intelligent Maintenance for Civil Engineering of Hebei Province Yanshan UniversityQinhuangdao 060000China Hebei Province Low-Carbon and Clean Building Heating Technology Innovation Center Yanshan UniversityQinhuangdao 060000China Department of Mechanics and Tianjin Key Laboratory of Nonlinear Dynamics and Control Tianjin UniversityTianjin 300072China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China

Metamaterials with simple artificial topological properties made from industrially produced single-phase materials have extraordinary innovation and *** this paper,we investigated wave propagation characteristics of a hexastarchiral lattice metamaterial with periodic assemblies and used the finite element(FE)method to study the band gap ***,in order to understand the mechanism of band gaps,we discussed the mode shapes of unit cells and found that the bending of the ligament and the overall rotation have a high correlation with the generation of omnidirectional band *** relationships bet ween geometric parameters and band gap properties have also been systematically studied,which demonstrated that the band gaps of the proposed metamaterial could be reasonably predicted through the evolution of geometric ***,the transmission characteristics of finite sandwich panel structures composed of periodic unit cells were calculated to verify the correctness of the band gap simulation results,which proved that the proposed artificial metastructure has potential application value in vibration and noise reduction projects.

关键词： Hexastarchiral lattice metamaterials Band gap properties Finite element method Rotational resonance

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Quantized Deep Neural Network Based Optimal control of Greenhouses on a Microcontroller

Quantized Deep Neural Network Based Optimal Control of Green...

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European control Conference (ECC)

作者： Kiran Kumar Sathyanarayanan Philipp Sauerteig Pablo Zometa Stefan Streif Automatic Control and System Dynamics Lab Technische Universität Chemnitz Chemnitz Germany Faculty of Engineering German International University Berlin Germany Department of Bioresources Fraunhofer Institute for Molecular Biology and Applied Ecology Giessen Germany

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Growing crops in controlled-Environment Agriculture (CEA) farms, such as greenhouses and vertical farms, can help in meeting the demands of urban centers and achieving climate goals. Recently, many advanced control techniques like Model Predictive control (MPC) and its variants have been developed for energy-efficient operation and minimization of resource utilization. However, real-time implementation of these advanced strategies come along with certain computational hardware requirements, thus, increasing the operating costs. In this work, we propose to learn the MPC policy of a greenhouse control by means of a Deep Neural Network (DNN) in order to be implemented on a low-cost microcontroller. Additionally, we use a feedback law to reduce undesired quantization effects. The efficiency of our approach is exemplified by means of a simulation study for greenhouse control.

关键词： Quantization (signal) Microcontrollers Optimal control Greenhouses Artificial neural networks Minimization Real-time systems

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Energy harvesting and speed sensing with a hybrid rotary generator for self-powered wireless monitoring

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Acta Mechanica Sinica 2024年第9期40卷 116-130页

作者： Zhixia Wang Hongyun Qiu Xuanbo Jiao Wei Wang Qichang Zhang Ruilan Tian Dongxing Cao School of Mechanical Engineering Tianjin UniversityTianjin 300350China Tianjin Key Laboratory of Nonlinear Dynamics and Control Tianjin 300350China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China Department of Mechanics Engineering Shijiazhuang Tiedao UniversityShijiazhuang 050043China Faculty of Materials and Manufacturing Beijing University of TechnologyBeijing 100124China

Real-time onboard health monitoring systems are critical for the railway industry to maintain high service quality and operational ***,the issue with power supplies for monitoring sensors persists,especially for freight trains that lack onboard ***,we propose a hybrid piezoelectric-triboelectric rotary generator(HPT-RG)for energy harvesting and vehicle speed *** HPT-RG incorporates a rotational self-adaptive technique that softens the equivalent stiffness,enabling the piezoelectric non-resonant beam to surpass resonance limitations in a low-frequency *** experiments demonstrate the feasibility of using the HPT-RG as an energy harvesting module to collect the rotational energy of the freight rail transport and power the wireless temperature *** allow multiple monitoring in confined spaces on trains,a triboelectric sensing module is added to the HPT-RG to sense the operation speed and mileage of ***,the generator exhibits favorable mechanical durability under more than 600 h of official testing on the train bogie *** proposed HPT-RG is essential for creating a truly self-powered,maintenance-free,and zero-carbon onboard wireless monitoring system on freight railways.

关键词： Energy harvesting Speed sensing Rotational self-adaptive technique Low-frequency Self-powered wireless monitoring

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Physics-informed neural networks for parameter learning of wildfire spreading

arXiv

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arXiv 2024年

作者： Vogiatzoglou, Konstantinos Papadimitriou, C. Bontozoglou, V. Ampountolas, K. System Dynamics Laboratory Department of Mechanical Engineering University of Thessaly Volos38334 Greece Transport Processes & Process Equipment Laboratory Department of Mechanical Engineering University of Thessaly Volos38334 Greece Automatic Control & Autonomous Systems Laboratory Department of Mechanical Engineering University of Thessaly Volos38334 Greece

Wildland fires pose a terrifying natural hazard, underscoring the urgent need to develop datadriven and physics-informed digital twins for wildfire prevention, monitoring, intervention, and response. In this direction of research, this work introduces a physics-informed neural network (PiNN) designed to learn the unknown parameters of an interpretable wildfire spreading model. The considered modeling approach integrates fundamental physical laws articulated by key model parameters essential for capturing the complex behavior of wildfires. The proposed machine learning framework leverages the theory of artificial neural networks with the physical constraints governing wildfire dynamics, including the first principles of mass and energy conservation. Training of the PiNN for physics-informed parameter identification is realized using synthetic data on the spatiotemporal evolution of one- and two-dimensional firefronts, derived from a high-fidelity simulator, as well as empirical data (ground surface thermal images) from the Troy Fire that occurred on June 19, 2002, in California. The parameter learning results demonstrate the predictive ability of the proposed PiNN in uncovering the unknown coefficients of the wildfire model in one- and two-dimensional fire spreading scenarios as well as the Troy Fire. Additionally, this methodology exhibits robustness by identifying the same parameters even in the presence of noisy data. By integrating this PiNN approach into a comprehensive framework, the envisioned physics-informed digital twin will enhance intelligent wildfire management and risk assessment, providing a powerful tool for proactive and reactive strategies. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

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control of entanglement of two coupled flux qubits by a non-resonant driving field 7

Control of entanglement of two coupled flux qubits by a non-...

引用

7th IEEE International Conference on Information Technology and Nanotechnology, ITNT 2021

作者： Bastrakova, M.V. Munyaev, V.O. Research Institute for Physics and Technology Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia Lobachevsky State University of Nizhny Novgorod Department of Control Theory and System Dynamics Nizhny Novgorod Russia

ISBN: (纸本)9781665432177

We study entanglement and multiphoton transitions in a system of coupled superconducting flux qubits under the action of an alternating drving field (the frequency of the external field is much higher than the frequency of qubit transitions). The positions of multiphoton transitions are found within the framework of the quasi-energy representation and the Floquet perturbation theory. It is shown that by tuning the external control field, it is possible to control the positions of the resonances and the measure of entanglement in the system. The influence of dissipation processes on multiphoton interference effects is studied. © 2021 IEEE.

关键词： Perturbation techniques

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Experimental Validation of Online Motion Planning for Semi-Autonomous Vehicles

Experimental Validation of Online Motion Planning for Semi-A...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Christoph Winter Ricardo De Castro Tilman Bünte Institute of System Dynamics and Control German Aerospace Center (DLR) Oberpfaffenhofen Germany Department of Mechanical Engineering University of California Merced Merced United States of America

ISBN: (纸本)9781665475884

This work describes the optimization of paths and velocity profiles for the usage in semi-autonomous vehicles. The focus of the optimization lies on an energy efficient motion while considering the driver’s longitudinal demands. The trade-off between travel time and energy consumption of the vehicle can be directly chosen by the driver. With help of a nonlinear model predictive control framework the global optimum of the velocity optimization with nonlinear constraints based on the vehicle’s physical limits is found. The online path planner together with the online velocity planner provide the input to the underlying vehicle’s control modules, as a basis for automated driving. The effectiveness of the proposed approach is shown via hardware-in-the-loop tests and real-world driving tests.

关键词： Energy consumption Propulsion Programming Energy efficiency Planning Optimization Vehicles

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SOIL FLOW ANALYSIS FOR PLANETARY ROVERS BASED ON PARTICLE IMAGE VELOCIMETRY AND DISCRETE ELEMENT METHOD 20

SOIL FLOW ANALYSIS FOR PLANETARY ROVERS BASED ON PARTICLE IM...

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20th International and 9th Americas Conference of the International Society for Terrain-Vehicle systems, ISTVS 2021

作者： Ono, Shoko Lichtenheldt, Roy Yoshida, Kazuya Department of Aerospace Engineering Tohoku University Aoba 6-6-01 Sendai980-8579 Japan Institute of System Dynamics and Control Münchener Straße 20 Weßling82234 Germany

ISBN: (纸本)9781942112525

Planetary rovers commonly have grouser wheels to improve locomotion performance on deformable terrains such as the surfaces of the Moon or Mars. The biggest difference between the wheel with grousers and without grousers is soil behavior underneath the wheel since the grousers shovel the sand. Hence, analyzing soil flow gives us beneficial information on wheel-soil interaction. The detailed investigation for micro-scale soil behavior and gravity effect, which are difficult to see in the laboratory test, contributes to further understanding of wheel-soil interaction mechanics. This paper presents a two-dimensional discrete element method (DEM) simulation to analyze soil flow beneath the grouser wheel. The soil flow in the simulation is validated by comparing it with that of the measurements, which is visualized by particle image velocimetry (PIV). The comparison results are discussed from four perspectives: 1) wheel slip ratio, 2) traces formed behind the wheel travels, 3) entrance and leaving angles of the grousers, 4) soil velocity field. The results indicate that DEM could describe the soil deformation. This work would contribute to further investigations of the state inside the soil by using developed DEM simulation. © ISTVS 2021. All rights reserved.

关键词： Velocity measurement

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Multi-objective Group Decision and Cooperative Planning Based on Preference and Fuzzy Measure 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Ma, Xiwen Xie, Wei Yang, Jingsong Zhang, Weidong Lu, Jinhui School of Oceanography Shanghai Jiao Tong University Shanghai China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography Ministry of Natural Resources Hangzhou China Department of Automation Shanghai Jiao Tong University Shanghai China Zhuhai China School of Information and Communication Engineering Hainan University Hainan Haikou China National Engineering Research Center of Ship and Shipping Control System Shanghai China Crossocean of Suzhou technology No. 218 East Oingdao Road Suzhou China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

To pursue interest balance and improve collaboration efficiency, this paper proposes a multi-agent cooperation method integrating decision-making and planning. Based on preference and fuzzy measures, this method can balance individual and group benefits under fuzzy uncertain environment. The equilibrium solution of a multi-agent multi-objective game, namely group decision-making (GDM) solution, can be obtained by the Gaussian oscillation particle swarm optimization (GOPSO) algorithm, which overcomes the dilemma of a multi-objective group game and improves the computational efficiency. Considering the smoothness and continuity of the trajectory, a heuristic motion planning (MP) generation model that satisfies the kinematic constraints and minimizes differential thrust is proposed, which improves the cooperation efficiency. To verify the performance of this proposed method, simulation results are presented and some comparative statements are given. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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