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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Bullock, John L. Trujillo, Anna C. Cheng, Sheng Hovakimyan, Naira Dynamic Systems and Control Branch NASA Langley Research Center HamptonVA23681 United States Department of Mechanical Science and Engineering University of Illinois Urbana-Champaign UrbanaIL61801 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper presents simulations of L1 adaptive controller on a multirotor vehicle for compensation of convective winds. There are increasing efforts to utilize unmanned vehicles for fighting wildfires, but such vehicles need to be able to compensate for convective updrafts and other uncertainties (e.g., wind shear and turbulence) caused by the wildfire. Other application domains, such as urban air mobility, also must account for convective or uncertain winds present in urban microclimates. Geometric controllers have great tracking performance properties in environments without uncertainties, but the tracking performance degrades when wind disturbances and external loads are present in the environment. Introducing L1 adaptive control into the controller architecture compensates for these wind disturbances and reduces the tracking error caused by such disturbances. The controller architecture is implemented on a small quadrotor. The simulations demonstrate the advantages of the L1 adaptive augmentation for a sample figure-eight trajectory while encountering unknown variable wind conditions with an external load. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Adaptive control systems

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Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Piloted Evaluation of a Fault Recovery System for an Aircraf...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Litt, Jonathan S. Sachs-Wetstone, Jonah J. Shane Sowers, T. Karl Owen, A. Bricker, Sophia M. Schaldenbrand, Anna Intelligent Control and Autonomy Branch NASA Glenn Research Center ClevelandOH44135 United States Intelligent Control and Autonomy Branch HX5 LLC Brook ParkOH44024 United States Intelligent Control and Autonomy Branch NovaTek Engineering ChardonOH44024 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aircraft propulsion

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Policy for Optimal Avoidance of Multiple Engagement Zones

Policy for Optimal Avoidance of Multiple Engagement Zones

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Milutinović, Dejan Von Moll, Alexander Weintraub, Isaac E. Casbeer, David Department of Electrical and Computer Engineering University of California Santa Cruz Santa CruzCA95064 United States Control Science Center Air Force Research Laboratory WPAFB OH45433 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This work formulates the feedback control strategies for vehicles to reach a goal point amongst a field of dynamic risk regions. Whereas previous work has considered deterministic versions of this problem, we consider the scenario in the context of uncertainty. This uncertainty could be due to unknown wind or other external disturbances. The risk regions’ dynamics are tightly coupled to the state of the vehicle and as a result the task of navigating through a field dynamically changes as the vehicle traverses through it. Rather than using a nonlinear program solver, the approach taken here is one of formulating the problem as a stochastic optimal control problem wherein a feedback control law is derived. This feedback control law allows a single or multiple vehicles to reach the desired goal location efficiently and with minimal risk incursion. When inside a risk region, there is a probability rate of the vehicle being neutralized. The stochastic dynamical system is modeled as a hybrid system, i.e., regime switching diffusion. The hybrid system is comprised of continuous spatial dynamics and discrete operational states corresponding to "normal" and "neutralized". The optimal control problem is discretized into a field of vehicle states and control. Using Value Iteration, the control signal at each discrete location is optimized, providing a feedback control strategy over the field. Following a discussion of the methods and approaches, this problem is formulated, simulations are performed, and conclusions and remarks are made © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Stochastic systems

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On the Cognitive Interface of Intelligent Systems Implementing the JSM Method of Automated research Support

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Automatic Documentation and Mathematical Linguistics 2025年第1期59卷 50-56页

作者： Shesternikova, O.P. Finn, V.K. Federal Research Center "Computer Science and Control " Russian Academy of Sciences Moscow Russia

Abstract: This article presents comments on the cognitive interface of an intelligent system (IS) implementing the JSM method of automated research support (JSM method ARS). The IS consists of an information environment, a Solver, and a cognitive interface. One component of the cognitive interface is a metatheoretical study (metatheoretical analysis) applied to the results generated by the Solver of IS. New procedures are proposed that expand the existing set of procedures in metatheoretical research: determining the type of the cause context (determining the influence of other causes in a situation of multiple causes) and recognizing the ternary of the cause (satisfaction with the ternary relation "object-set of obstacles (brakes)-effect") for empirical preregularities (EPRs) and, accordingly, empirical regularities (ERs), a superposition of EPRs. An example from a study of type 3c diabetes is given. © Allerton Press, Inc. 2025.

关键词： Automation

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Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling Under Data Governance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 351-361页

作者： Qin, Zhaoming Dong, Nanqing Liu, Di Wang, Zhefan Cao, Junwei EPFL Automatic Control Laboratory Lausanne1015 Switzerland Shanghai Artificial Intelligence Laboratory Shanghai200232 China Tsinghua University Department of Electrical Engineering Beijing100084 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China

As a data-driven approach, multi-agent reinforcement learning (MARL) has made remarkable advances in solving cooperative residential load scheduling problems. However, centralized training, the most common paradigm for MARL, limits large-scale deployment in communication-constrained cloud-edge environments. As a remedy, distributed training shows unparalleled advantages in real-world applications but still faces challenge with system scalability, e.g., the high cost of communication overhead during coordinating individual agents, and needs to comply with data governance in terms of privacy. In this work, we propose a novel MARL solution to address these two practical issues. Our proposed approach is based on actor-critic methods, where the global critic is a learned function of individual critics computed solely based on local observations of households. This scheme preserves household privacy completely and significantly reduces communication cost. Simulation experiments demonstrate that the proposed framework achieves comparable performance to the state-of-the-art actor-critic framework without data governance and communication constraints. © 2023 IEEE.

关键词： Reinforcement learning

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DADAN: Dynamic-Augmented and Density-Aware Network for Accurate 3-D Object Detection With 4-D Radar

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IEEE Sensors Journal 2025年第6期25卷 10272-10286页

作者： Wang, Xingzheng Li, Jiahui Wu, Jianbin Wu, Shaoyong Li, Lihua Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen Technology University Guangdong-Hongkong-Macao Critical Optical Components Precision Manufacturing Research Center Sino-German College of Intelligent Manufacturing Shenzhen518118 China

The cost-effective automotive 4-D radar is emerging as a feasible solution for 3-D object detection in autonomous driving scenarios. However, point clouds generated by 4-D radar are typically sparse. Current methods encounter challenges in resolving the foreground-background confusion in sparse point clouds due to: 1) the underutilization of the unique dynamic information (velocity and intensity) of 4-D radar points;and 2) the density variations of point clouds where they are near-dense-far-sparse, exacerbating the confusion. Therefore, we propose a dynamic-augmented and density-aware network (DADAN) to address these challenges by: 1) assigning high weights to foreground points based on dynamic information and enhancing their feature encoding to reduce confusion effectively;and 2) utilizing attention mechanisms along with density information to adaptively address exacerbated confusion caused by density variations. The DADAN comprises a dynamic-augmented encoding network, a density-aware backbone, and a detection head. The encoding network incorporates a dynamic-augmented encoding module (DAEM) that assigns high weights to foreground points based on velocity and intensity data to improve their feature encoding. Notably, foreground points typically exhibit distinct dynamic information compared to background points, distinguishing them from the background. The backbone network incorporates an attention mechanism along with density information to generate density-aware features. The detection head is responsible for 3-D bounding boxes and object categories. The experimental results on various public datasets demonstrate the superior performance of the proposed method compared to existing approaches. These results illustrate that the DADAN effectively addresses the issue of confusion, accurately detecting objects in complex scenes. © 2001-2012 IEEE.

关键词： Object detection

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Terahertz time-of-flight tomography algorithm for different curvature samples

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Optics Express 2025年第7期33卷 15095-15109页

作者： Zhou, Yu Li, Quanyong Cui, Zongyu Zhang, Jiyang Ren, Jiaojiao Zhang, Dandan Gu, Jian Li, Haoxiang Lin, Zihao Key Laboratory of Optoelectronic Measurement and Control and Optical Information Transmission Technology Ministry of Education Changchun University of Science and Technology Changchun130022 China School of Optoelectronic Engineering Changchun University of Science and Technology Changchun130022 China Zhongshan Research Institute Changchun University of Science and Technology Zhongshan528403 China

Traditional guide rail-based terahertz reflection tomography works well with planar samples and complements transmission tomography. Most imaging methods perform effectively with plane-like or simple curvature samples. However, these methods are ineffective for complex shapes due to the challenges of dealing with internal corrections and stitching errors. To address the above issues, terahertz time-of-flight tomography is applied to the prepared samples with abnormal curvature using a rotating scanning array and "point cloud splicing" method. This approach enables comprehensive sample information collection and resolves the inner layer point cloud position correction challenge. A radial distance point cloud down-sampling method is proposed to reduce the impact of overlapping point clouds on reconstruction accuracy. After down-sampling, the outer layer reconstruction error reduces to 0.22%. Poisson surface reconstruction further enhances the intuitiveness of imaging results, and the reconstruction accuracy is 0.01 mm. This study broadens the application of terahertz time-of-flight tomography and offers a different approach for reflection tomography. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Surface reconstruction

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HPO-BiLSTM Based on Causal Analysis of Upstream and Downstream Industries Load Forecasting Method 19th

HPO-BiLSTM Based on Causal Analysis of Upstream and Downstre...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Liu, Yaoxian Su, Jiahao Qiu, Min Chen, Jingwen School of Electrical and Control Engineering Shaanxi University of Science and Technology Xi’an710021 China China Electric Power Research Institute Limited BeiJing100192 China

ISBN: (纸本)9789819646746

Due to the lack of causality between upstream and downstream industries in the existing load forecasting research, the accuracy of load forecasting between industries is poor. Therefore, this paper proposes an HPO-BiLSTM industry load forecasting method based on causal analysis. Firstly, convergence cross-mapping algorithm is used to identify the causal relationship between ferroalloy industry and related industries, and typical industries with strong causality are selected. Secondly, the original load data is decomposed by an improved adaptive noise complete empirical mode decomposition method. Finally, the hunter and prey algorithm is used to optimize the bidirectional long and short term network, and the decomposed load data is predicted. Finally, the accuracy of the proposed method is compared with that of XGBoost and LSTM prediction models. Experiments show that the proposed method can effectively extract the relevant features of different industries in the load prediction of ferroalloy industry. The prediction accuracy is significantly improved, which provides important support for rational planning and stable operation of urban power grid. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Causal analysis HPO-BiLSTM ICEEMDAN industry load forecasting

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Using an optical fiber passive depolarizer to suppress the polarization dependence of stimulated Raman scattering gain in hydrogen sensor system 4

Using an optical fiber passive depolarizer to suppress the p...

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4th International Computational Imaging Conference, CITA 2024

作者： Shuzhi, Yao Xuan, Zheng Yong, Yang Meng, Jiang Hui, Gao Meng, Zhang Xuefeng, Wang Beijing Institute of Aerospace Control Device Beijing100094 China Beijing Optical Fiber Sensing System Engineering Technology Research Center Beijing100094 China

ISBN: (纸本)9781510688834

Optical fiber hydrogen sensors have recently received great attention because of the advantages of essential safety, anti-electromagnetic interference, corrosion resistance, suitable for long distance detection and so on. A new type of optical fiber hydrogen sensors based on stimulated Raman scattering spectroscopy and nanofiber was proposed several yeas ago which can realize ultra-fast, ultra-sensitive hydrogen detection with ultra-wide dynamic range. However, the Raman gain depends on the polarization states of the pump and Stokes beams and the Raman signal will drift when the fiber status or the environment temperature are changed. In this paper, we propose and demonstrate an optical fiber passive depolarizer to suppress the polarization dependence of stimulated Raman scattering gain in the aforementioned hydrogen sensor system. The depolarizer mainly consists of two fiber polarization beam splitters(PBSs) and a piece of delay fiber. The angle of incidence for any PBS is 45° and the delay fiber length is much longer than the coherent length of the input beam. The input beam is split into two beams by PBS1 one of which transfers through the delay fiber. Then these two beams are combined by PBS2 to obtain the output beam composed of two orthogonal beams with equal power, and their phase relationship changes randomly. By inserting the depolarizer into the pump beam path, the Raman signal will not be influenced by the changes of the fiber status or the environment temperature. This achievement would be very useful for real application of the hydrogen sensor in long distance detection and multi-channel sensing system. © 2025 SPIE.

关键词： Stimulated Raman scattering

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Copper-catalyzed Larock-type cyclization/debenzylation of yne-allylic esters with aliphatic amines

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science China Chemistry 2025年

作者： Rongkang Huang Yuepeng Lu Feng Xu Jianhang Huang Cuiju Zhu Hao Xu Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction State Key Laboratory of Green Pesticide College of Chemistry Central China Normal University

Herein, we describe a strategy for constructing pyrroles via a copper-catalyzed [4 + 1] annulation of yne-allylic esters and aliphatic amines. The key innovation of this approach is the development of copper-ammonium intermediates that facilitate selective C–N bond cleavage under mild conditions. This method demonstrates broad applicability, accommodating both aliphatic secondary amines and aliphatic primary amines, while exhibiting excellent tolerance toward a wide range of functional groups. Furthermore, the ease of subsequent transformations underscores its potential utility in the synthesis of bioactive compounds. Preliminary mechanistic investigations suggest the involvement of a copper-ammonium species, providing insight into the reaction's underlying process.

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