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11th International Conference on Learning Representations, ICLR 2023

作者： Beintema, Gerben I. Schoukens, Maarten Tóth, Roland Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

Continuous-time (CT) modeling has proven to provide improved sample efficiency and interpretability in learning the dynamical behavior of physical systems compared to discrete-time (DT) models. However, even with numerous recent developments, the CT nonlinear state-space (NL-SS) model identification problem remains to be solved in full, considering common experimental aspects such as the presence of external inputs, measurement noise, latent states, and general robustness. This paper presents a novel estimation method that addresses all these aspects and that can obtain state-of-the-art results on multiple benchmarks with compact fully connected neural networks capturing the CT dynamics. The proposed estimation method called the subspace encoder approach (SUBNET) ascertains these results by efficiently approximating the complete simulation loss by evaluating short simulations on subsections of the data, by using an encoder function to estimate the initial state for each subsection and a novel state-derivative normalization to ensure stability and good numerical conditioning of the training process. We prove that the use of subsections increases cost function smoothness together with the necessary requirements for the existence of the encoder function and we show that the proposed state-derivative normalization is essential for reliable estimation of CT NL-SS models. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Cost functions

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Multi-Condition Fault Diagnosis of Dynamic systems: A Survey, Insights, and Prospects

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 15728-15744页

作者： Han, Pengyu Liu, Zeyi He, Xiao Ding, Steven X. Zhou, Donghua Tsinghua University Department of Automation Beijing 100084 China University of Duisburg-Essen Institute for Automatic Control and Complex Systems Duisburg 47057 Germany Southeast University School of Automation Nanjing 210096 China

With the increasing complexity of industrial production systems, accurate fault diagnosis is essential to ensure safe and efficient system operation. However, due to changes in production demands, dynamic process adjustments, and complex external environmental disturbances, multiple operating conditions frequently arise during production. The multi-condition characteristics pose significant challenges to traditional fault diagnosis methods. In this context, multi-condition fault diagnosis has gradually become a key area of research, attracting extensive attention from both academia and industry. This paper aims to provide a systematic and comprehensive review of existing research in the field. Firstly, the mathematical definition of the problem is presented, followed by an overview of the current research status. Subsequently, the existing literature is reviewed and categorized from the perspectives of single-model and multi-model approaches. In addition, typical real-world application scenarios are then summarized and analyzed. Finally, the key challenges and prospects in the field are thoroughly discussed. © 2004-2012 IEEE.

关键词： artificial intelligence data-driven Fault diagnosis multi-condition

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Adaptive Unscented Kalman Filter Based Sensor Fusion for Aircraft Positioning Relative to Unknown Runway

Adaptive Unscented Kalman Filter Based Sensor Fusion for Air...

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

作者： Ghosh, Nabarun Maity, Arnab Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Maharashtra Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper proposes an estimator to provide precise position, velocity, and orientation for a landing aircraft relative to the runway based on image sensors, IMU sensor data, and barometric sensor measurements. This work excludes GPS data, as it is expected that the proposed estimator can be used for fault detection in GPS and instrument landing systems. The runway is unknown, and hence, its width is estimated online. An adaptive UKF-based approach is adopted to estimate the states. In order to verify the nearer-to-practical performance and accuracy of bias estimation, realistically simulated data that constitute noises and biases from the sensors are taken into consideration. The proposed approach provides a solution for nonlinear state estimation in the presence of measurement noises that are non-additive. In addition to this, it provides estimates of the unknown measurement noise covariance. A comparative study is conducted between the conventional UKF and the proposed AUKF to analyze the adopted approach. Results show that the proposed algorithm gives comparable estimation results and faster convergence than the conventional UKF. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Fault detection

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Fair Artificial Currency Incentives in Repeated Weighted Congestion Games: Equity vs. Equality 63

Fair Artificial Currency Incentives in Repeated Weighted Con...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Pedroso, Leonardo Agazzi, Andrea Heemels, W.P.M.H. Maurice Salazar, Mauro Eindhoven University of Technology Control Systems Technology Section Netherlands Universita di Pisa Mathematics Department Pisa Italy Italy

ISBN: (纸本)9798350316339

When users access shared resources in a selfish manner, the resulting societal cost and perceived users' cost is often higher than what would result from a centrally coordinated optimal allocation. While several contributions in mechanism design manage to steer the aggregate users choices to the desired optimum by using monetary tolls, such approaches bear the inherent drawback of discriminating against users with a lower income. More recently, incentive schemes based on artificial currencies have been studied with the goal of achieving a system-optimal resource allocation that is also fair. In this resource-sharing context, this paper focuses on repeated weighted congestion game with two resources, where users contribute to the congestion to different extents that are captured by individual weights. First, we address the broad concept of fairness by providing a rigorous mathematical characterization of the distinct societal metrics of equity and equality, i.e., the concepts of providing equal outcomes and equal opportunities, respectively. Second, we devise weight-dependent and time-invariant optimal pricing policies to maximize equity and equality, and prove convergence of the aggregate user choices to the system-optimum. In our framework it is always possible to achieve system-optimal allocations with perfect equity, while the maximum equality that can be reached may not be perfect, which is also shown via numerical simulations. © 2024 IEEE.

关键词： Costs

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CubeSat attitude control via linear quadratic regulator (LQR) 20

CubeSat attitude control via linear quadratic regulator (LQR...

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20th International Conference on Aerospace Sciences and Aviation technology, ASAT 2023

作者： Helmy, M. Hafez, A.T. Ashry, M. Optoelectronics and Automatic Control Systems Department Military Technical College Cairo Egypt Aircraft Armament Department Military Technical College Cairo Egypt

The interest in space-related activities has grown recently on a global scale. The determination and control of attitude are necessary all space duties. As it affects the satellites mission accuracy, many researches are related to it. Attitude control systems (ACS) design and modelling are represented in this paper. The mathematical models for CubeSat and reaction wheels that act as actuator and the proposed optimal control system are introduced. The proposed controller is applied to control and stabilize the CubeSat through a set of reaction wheels. The simulation results show the superior results of the proposed controller compared with traditional control systems in the presence of external disturbances and white noise. The withdraws of each control system are presented through the simulation results. The main contribution in this paper is solving the attitude control problem for a CubeSat using LQR approach in the presences of disturbances and noise. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Attitude control

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A frequency domain property driven search method for echo state network structures 6

A frequency domain property driven search method for echo st...

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6th International Conference on Intelligent control, Measurement and Signal Processing, ICMSP 2024

作者： Zhang, Zhaozhao Li, Bofan Zhu, Yingqin Xi'an University of Science and Technology College Computer Science and Technology Xi'an China CINVESTAV-IPN National Polytechnic Institute Department of Control Automatic Mexico City Mexico

ISBN: (纸本)9798331516550

To overcome the limitations of conventional echo state networks (ESN), such as redundant connections and insufficient frequency-domain feature extraction, this paper proposes a frequency-domain feature architecture search-based ESN (FS-ESN). Leveraging a frequency response fitness function, FS-ESN dynamically optimizes reservoir structures and incorporates frequency-domain features aligned with target tasks. Experimental results demonstrate that FS-ESN significantly improves feature extraction, adaptability, and predictive performance, outperforming traditional ESN models in task-specific applications. © 2024 IEEE.

关键词： Frequency domain analysis

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A Methodology Establishing Linear Convergence of Adaptive Gradient Methods Under PL Inequality 27

A Methodology Establishing Linear Convergence of Adaptive Gr...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Chakrabarti, Kushal Baranwal, Mayank Tata Consultancy Services Research Mumbai India Department of Systems & Control Engineering Indian Institute of Technology India

ISBN: (纸本)9781643685489

Adaptive gradient-descent optimizers are the standard choice for training neural network models. Despite their faster convergence than gradient-descent and remarkable performance in practice, the adaptive optimizers are not as well understood as vanilla gradient-descent. A reason is that the dynamic update of the learning rate that helps in faster convergence of these methods also makes their analysis intricate. Particularly, the simple gradient-descent method converges at a linear rate for a class of optimization problems, whereas the practically faster adaptive gradient methods lack such a theoretical guarantee. The Polyak-Lojasiewicz (PL) inequality is the weakest known class, for which linear convergence of gradient-descent and its momentum variants has been proved. Therefore, in this paper, we prove that AdaGrad and Adam, two well-known adaptive gradient methods, converge linearly when the cost function is smooth and satisfies the PL inequality. Our theoretical framework follows a simple and unified approach, applicable to both batch and stochastic gradients, which can potentially be utilized in analyzing linear convergence of other variants of Adam. © 2024 The Authors.

关键词： Cost functions

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Online One-Dimensional Magnetic Field SLAM with Loop-Closure Detection

Online One-Dimensional Magnetic Field SLAM with Loop-Closure...

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2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent systems, MFI 2024

作者： Kok, Manon Solin, Arno Delft University of Technology Delft Center for Systems and Control Netherlands Aalto University Department of Computer Science Finland

ISBN: (纸本)9798350368031

We present a lightweight magnetic field simultaneous localisation and mapping (SLAM) approach for drift correction in odometry paths, where the interest is purely in the odometry and not in map building. We represent the past magnetic field readings as a one-dimensional trajectory against which the current magnetic field observations are matched. This approach boils down to sequential loop-closure detection and decision-making, based on the current pose state estimate and the magnetic field. We combine this setup with a path estimation framework using an extended Kalman smoother which fuses the odometry increments with the detected loop-closure timings. We demonstrate the practical applicability of the model with several different real-world examples from a handheld iPad moving in indoor scenes. © 2024 IEEE.

关键词： Magnetic fields

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Optimal Crop Rotations subject to Weed Dynamics: Exponential Stability and Nonlinear Programming 63

Optimal Crop Rotations subject to Weed Dynamics: Exponential...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Jong, Maarten De McAllister, Koty Giordano, Giulia Delft University of Technology Delft Center for Systems and Control Netherlands University of Trento Department of Industrial Engineering Italy

ISBN: (纸本)9798350316339

Agricultural production of annual crops is often hampered by annual weeds, which compete with planted crops and persist through the collection of dormant seeds in the soil called the weed seed bank. Conventional weed management relies heavily on chemical herbicides, which are not sustainable. A complementary method that reduces the need for herbicides is 'cultural control', in which the crop rotation is designed in part to manage the weed population. We propose a methodology that optimizes the crop rotation, here defined as periodic crop planting densities, subject to periodic weed dynamics. We adopt a well-established model of discrete-time annual weed seed bank dynamics with crop planting density inputs, and show that any periodic weed seed bank trajectory corresponding to a periodic crop rotation is globally exponentially stable. This guarantees convergence to the optimal periodic trajectory obtained by solving a nonlinear optimal control problem with periodic constraints, which we formulate as a nonlinear program. © 2024 IEEE.

关键词： Crop rotation

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Open-loop equilibrium seeking in two-agent noncooperative linear-quadratic dynamic game with asymmetric horizon length

Open-loop equilibrium seeking in two-agent noncooperative li...

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作者： Wasa, Yasuaki Tanaka, Taichi Hayakawa, Tomohisa Department of Electrical Engineering and Bioscience Waseda University Tokyo Japan Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan

This article proposes an iterative-based algorithm for open-loop equilibrium seeking in a two-agent noncooperative dynamic game. The finite-horizon dynamic games handled in almost all existing articles assume the common prediction horizon length. From the viewpoint of divergence and differences in personal values, it is socially rational to solve the equilibrium of the games with asymmetric prediction horizon length. We thus propose an open-loop equilibrium-seeking algorithm without the private knowledge of the other agent's horizon information through a receding-horizon linear-quadratic game. Our proposed algorithm is based on iterative optimization. Each agent obtains its own best response control strategy while estimating the other agent's state feedback gain from the state information and guaranteeing the stability of the whole system. We also discuss the performance of the proposed equilibrium-seeking algorithm through numerical examples. © 2023 Chinese automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Iterative methods

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