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11th International Conference on Learning Representations, ICLR 2023

作者： Chen, Shuangshuang Ding, Sihao Karayiannidis, Yiannis Björkman, Mårten School of Electrical Engineering and Computer Science Royal Institute of Technology Sweden AI Lab Volvo Car Corporation Sweden Department of Automatic Control Lund University Sweden

Normalizing flows (NFs) have been shown to be advantageous in modeling complex distributions and improving sampling efficiency for unbiased *** this work, we propose a new class of continuous NFs, ascent continuous normalizing flows (ACNFs), that makes a base distribution converge faster to a target *** solving such a flow is non-trivial and barely possible, we propose a practical implementation to learn flexibly parametric ACNFs via ascent regularization and apply it in two learning cases: maximum likelihood learning for density estimation and minimizing reverse KL divergence for unbiased sampling and variational *** learned ACNFs demonstrate faster convergence towards the target distributions, therefore, achieving better density estimations, unbiased sampling and variational approximation at lower computational ***, the flows show to stabilize themselves to mitigate performance deterioration and are less sensitive to the choice of training flow length T. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Maximum likelihood estimation

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Current-limiting control of interlinking converter to maintain power balance in hybrid microgrids

Current-limiting control of interlinking converter to mainta...

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2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Skentzos, Panagiotis Konstantopoulos, George C. The University of Sheffield Dept. of Automatic Control and Systems Engineering Sheffield United Kingdom University of Patras Dept. of Electrical and Computer Engineering Patra Greece

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

In this paper, a novel nonlinear current-limiting controller that maintains the desired power balance in a hybrid microgrid, is proposed for interlinking converters (ICs). The RMS value of the IC current is analytically proven to remain below a desired maximum value at all times using nonlinear ultimate boundedness theory, without limiting separately the d- and q-axis current components and without using adaptive saturation units, as done in conventional approaches. Furthermore, the stability of the closed loop system is investigated through root locus analysis for different values of the controller gain. Finally, the performance of the proposed control scheme is validated through detailed simulation results of an interlinking converter connected to both an AC and a DC subgrid. © 2022 IEEE.

关键词： controllers

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Reference Model Design in Multiple Timescale Adaptive control

Reference Model Design in Multiple Timescale Adaptive Contro...

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

作者： Eves, Kameron Valasek, John Electrical and Computer Engineering Engineering Department Utah Tech University Saint GeorgeUT84770 United States Vehicle Systems and Control Laboratory Aerospace Engineering Department Texas A and M University College StationTX77843-3141 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The method [K]control of Adaptive Multiple-timescale systems (KAMS) has been used as a method of adaptive control for systems with states that evolve at vastly different rates and with uncertain parameters. Prior research on KAMS has shown a relationship between the asymptotic behavior of the reference models and the behavior of the full-order closed-loop system. Poor reference model design can cause steady-state error or instability even if that reference model is acceptable in a single timescale context, due to adverse feedback between the reference models and the fast-state manifold. This paper simplifies KAMS control design and provides insight into multiple timescale reference models by identifying design considerations for the fast and slow reference models. For fast reference models, it is shown that the stability proofs used in KAMS control design necessarily require the manifold to be an asymptotically stable equilibrium of the fast reference model, despite prior work that allowed other possibilities. In the case of a slow reference model that is not asymptotically stable to its reference signal, it is common for the inner connection conditions to be dependent on the reference signal. This can cause the interconnection conditions to be ill-formatted for the application of the stability proofs used in KAMS control design. This paper addresses that case and proposes the use of Raffoul’s condition as a method to prove stability in the sense of Lyapunov. A linear quadrotor attitude stabilization problem is used as a framework for the slow reference model analysis. Results presented in the paper show that 1) the asymptotic stability of the fast reference model is a necessary condition for the KAMS stability proofs used in prior work and 2) Raffoul’s condition is a sufficient condition for Lyapunov sense stability even when the inner connection conditions are ill-formatted for the KAMS stability proofs used in prior work. © 2025, American Institute of Aeronautics

关键词： Model reference adaptive control

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Measurement of Reflection and Shielding Effectiveness of Electromagnetic Fields in Construction Materials with Subsequent Calculation of Absorption 5

Measurement of Reflection and Shielding Effectiveness of Ele...

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5th IEEE International Conference on Modern Electrical and Energy System, MEES 2023

作者： Pavlik, Marek Melnykov, Viacheslav Technical University of Košice Department of Electric Power Engineering Košice Slovakia Kremenchuk Mykhailo Ostrohradskyi National University Department of Systems of Automatic Control and Electric Drive Kremenchuk Ukraine

ISBN: (纸本)9798350359787

In today's world of wireless technologies, we observe a proliferation of devices that communicate and operate wirelessly. All these devices emit electromagnetic radiation, which also penetrates the human body. Given the current technologies, it is not possible to completely prevent the impact of electromagnetic radiation on humans. However, we can mitigate the effects of electromagnetic radiation by choosing the right shielding material. One natural shielding material, for example, is a building. Therefore, in this article, we focused on research in the field of electromagnetic field shielding, reflection, and absorption in building structures. The article describes a measurement method for determining the effectiveness of shielding and reflection of electromagnetic fields. Subsequently, based on these measurements, the absorption of electromagnetic fields can be calculated. © 2023 IEEE.

关键词： Electromagnetic fields

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Binary Stochastic Flip Optimization for Training Binary Neural Networks

Binary Stochastic Flip Optimization for Training Binary Neur...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Shibuya, Tatsukichi Inoue, Nakamasa Kawakami, Rei Sato, Ikuro Department of Computer Science Institute of Science Tokyo Tokyo Japan Department of Systems and Control Engineering Institute of Science Tokyo Tokyo Japan Denso IT Laboratory Tokyo Japan

ISBN: (纸本)9798350368741

For deploying deep neural networks on edge devices with limited resources, binary neural networks (BNNs) have attracted significant attention, due to their computational and memory efficiency. However, once a neural network is binarized, finetuning it on edge devices becomes challenging because most conventional training algorithms for BNNs are designed for use on centralized servers and require storing real-valued parameters during training. To address this limitation, this paper introduces binary stochastic flip optimization (BinSFO), a novel training algorithm for BNNs. BinSFO employs a parameter update rule based on Boolean operations, eliminating the need to store real-valued parameters and thereby reducing memory requirements and computational overhead. In experiments, we demonstrated the effectiveness and memory efficiency of BinSFO in finetuning scenarios on six image classification datasets. BinSFO performed comparably to conventional training algorithms with a 70.7% smaller memory requirement. Code is released at https://***/TatsukichiShibuya/ICASSP2025_BinSFO. © 2025 IEEE.

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Secure-by-Construction Synthesis for control systems

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IEEE Transactions on automatic control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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Optimization Design and Dynamic Compensation Strategy of Inverter Parallel Virtual Impedance Based on Residual Generator 7

Optimization Design and Dynamic Compensation Strategy of Inv...

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7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023

作者： Hu, Changbin Huang, Haiyang Luo, Shanna Wang, Huiru Li, Xuecheng Lu, Heng North China University of Technology School of Electrical and Control Engineering Beijing China Beijing Kedong Electric Power Control System Co. Ltd Beijing China University of Duisburg-Essen Department of Automatic Control and Complex Systems Germany

ISBN: (纸本)9798350345094

To solve the power imbalance problem caused by the difference between the equivalent impedance of the inverter and the line impedance, and the power quality problem caused by the disturbance of load mutation, unbalanced load and nonlinear load, this paper proposes a closed-loop feedback dynamic compensation strategy based on the equivalent virtual impedance of the residual generator. Firstly, based on the parallel topology of inverters, a quasi-steady-state model is established on the dq axis. Based on the model, the power imbalance caused by the difference of output impedance and line impedance of different inverters and the power quality problems caused by load switching, unbalanced load, nonlinear load and other disturbances in parallel inverters are ***, a residual generator is established based on the inverter model. A virtual impedance equivalent controller Qvir(S) based on the residual generator is designed by the Luenberger observer principle. The disturbance information is fed back in real time through the feedback structure, and then the virtual impedance is adjusted to realize the power sharing of the inverter parallel system. Then, based on Euler parameterization and coprime factorization theory, a dynamic compensation architecture based on residual generator is designed. The transfer function of the dynamic compensation controller Qcom (S) is obtained by model matching to realize the steady-state operation of parallel inverters and the improvement of system power quality. Finally, the effectiveness of the proposed architecture is verified on the experimental platform. © 2023 IEEE.

关键词： Power quality

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Robust Car-Following control of Connected and Autonomous Vehicles: A Stochastic Model Predictive control Approach

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Zhang, Peiyu Tian, Daxin Zhou, Jianshan Chang, Mai Duan, Xuting Zhao, Dezong Cao, Dongpu Leung, Vicor C.M. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China James Watt School of Engineering University of Glasgow Glasgow U.K Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Computer Science and Software Engineering Shenzhen University Shenzhen China

Vehicle platooning has attracted growing attention for its potential to enhance traffic capacity and road safety. This paper proposes an innovative distributed Stochastic Model Predictive control (SMPC) for a vehicle platoon system to enhance the robustness and safety of the vehicles in uncertain traffic environments. In particular, considering the similarity between the acceleration or deceleration behaviour of neighbouring vehicles and the spring-scale properties, we use a two-mass spring system for the first time to construct an uncertain dynamic model of a formation system. In the presence of uncertain perturbations with known distributional attributes (expectation, variance), we propose an objective function in the form of expectation along with probabilistic chance constraints. Subsequently, a state feedback control mechanism is devised accordingly. Under the cumulative probability distribution function of stochastic perturbations, we theoretically derive a computationally tractable equivalent of the SMPC model. Finally, simulation experiments are designed to validate the control performance of the SMPC platoon controllers, along with an analysis of the stability performance under varying probabilities. The experimental findings demonstrate that the model can be efficiently solved in real-time with appropriately chosen prediction horizon lengths, ensuring robust and safe longitudinal vehicle formation control. IEEE

关键词： Random processes

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Reinforcement Learning-Based Output Stabilization control for Nonlinear systems With Generalized Disturbances

Reinforcement Learning-Based Output Stabilization Control fo...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Zezhi Tang J Anthony Rossiter Yi Dong George Panoutsos Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Electronics and Computer Science University of Southampton Southampton United Kingdom

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

This paper proposes a new disturbance observer (DO)-based reinforcement learning (RL) control approach for nonlinear systems with unmatched (generalized) disturbances. While a nonlinear disturbance observer (NDO) is utilized to measure the plant uncertainties, disturbances can exist in the plant via distinct channels from those of the control signals; so-called mismatched disturbances are theoretically difficult to attenuate within the channel of the system's states. A generalized disturbance observer-based compensator is implemented to address the uncertainty cancellation problem by removing the influence of uncertainties from the output channels. Con-currently, a composite actor-critic RL scheme is utilized for approximating the optimal control policy as well as the ideal value function pertaining to the compensated system by solving a Hamilton-Jacobi-Bellman (HJB) equation for both online and offline iterations simultaneously. Stability analysis verifies the convergence of the proposed framework. Simulation results are included to illustrate the effectiveness of the proposed scheme.

关键词： Uncertainty Simulation Measurement uncertainty Optimal control Estimation Reinforcement learning Disturbance observers

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Analysis of Texture Synthesis Algorithms in computer Graphics

Analysis of Texture Synthesis Algorithms in Computer Graphic...

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2022 Conference of Russian Young Researchers in Electrical and Electronic engineering, ElConRus 2022

作者： Gurenko, Vladimir V. Eliseev, Vyacheslav A. Usmanov, Maxim O. Selezneva, Maria S. Bauman Moscow State Technical University Department of Computer Systems and Networks Moscow Russia Bauman Moscow State Technical University Department of Automatic Control Systems Moscow Russia

ISBN: (纸本)9781665409933

The use of computer graphics methods is associated with the ongoing problem of texture synthesis. There are two groups of approaches to this problem. The first one is the creating textures by a digital artist using such software tools as Substance Painter. The second group includes automatic methods based on specialized algorithms. Some examples include synthesis using non-parametric sampling, as well as machine learning algorithms based on PSGAN. This paper provides a comparative analysis based on quality and performance criteria of texture synthesis algorithms. It is worth to mention that the difficulty of assessing the quality of synthesis is caused by the lack of a formal quantitative metric. The authors made conclusions about the preferred fields for application of the analyzed algorithms. The results of this survey can be used to optimize the production activities of digital art studios in terms of the time it takes to make textures. © 2022 IEEE.

关键词： computer graphics

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