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2023 IEEE Conference on control technology and Applications, CCTA 2023

作者： Jung, Hanul Tacx, Paul Oomen, Tom Oh, Sehoon Dgist Department of Robotics Engineering Daegu42988 Korea Republic of Eindhoven University of Technology Control Systems Technology Group Department of Mechanical Engineering P.O. Box 513 Eindhoven5600 MB Netherlands

ISBN: (纸本)9798350335446

In this paper, novel parametric identification is addressed by the disturbance observer (DOB) relevant algorithm. To fully utilize the disturbance observer, a proper nominal model, which is a parametric model, is essential. The control performance of the DOB can be checked based on the robust stability criterion, which is related to the modeling error and the desired bandwidth of the DOB. Consequently, it is beneficial to evaluate the parametric model in the system identification procedure. Therefore, this paper proposes a novel disturbance observer-relevant system identification algorithm based on the robust stability criterion of the disturbance observer. The effectiveness of the proposed method is validated by showing the numerical simulations under specific conditions. © 2023 IEEE.

关键词： Stability criteria

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Optimal Stopping Problems in Low-Dimensional Feature Spaces: Lossless Conditions and Approximations

Optimal Stopping Problems in Low-Dimensional Feature Spaces:...

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IEEE Conference on Decision and control

作者： M.J.T.C. van Zutphen W.P.M.H. Heemels D.J. Antunes Department of Mechanical Engineering Control Systems Technology Group Eindhoven University of Technology The Netherlands

Optimal control problems can be solved by dy-namic programming. However, this method suffers from the curse of dimensionality. To resolve this, simplified versions of the original problem are often constructed in lower-dimensional feature spaces, leading to approximate policies. Yet, the connections between the original and the approximate policy and costs are rarely formalized. This paper addresses this challenge for optimal stopping problems. We start by providing conditions for lossless feature representations. This means that from an optimal policy obtained in feature space, an optimal policy in the original space can be constructed. Then, we search for modified versions of the original problem that (i) admit a lossless feature representation of far lower dimension; and (ii) provide upper and lower bounds on the optimal cost of the original problem. We can then use policies obtained in feature space using these modified problems to provide approximate policies for the original problem that are guaranteed to perform better than or equal to this aforementioned cost upper bound. We apply our tools in a high-dimensional precision farming intervention problem, where our tools allow for a dramatic decrease in complexity with only a small increase in the cost.

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Complexity-Bounded Relaxed Dynamic Programming

Complexity-Bounded Relaxed Dynamic Programming

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IEEE Conference on Decision and control

作者： R.M. Beumer M.J.G. Van De Molengraft D.J. Antunes Department of Mechanical Engineering Control Systems Technology Group Eindhoven University of Technology The Netherlands

The idea behind relaxed dynamic programming for optimal control problems is to settle with a suboptimal but simpler control policy that guarantees a cost within a fixed constant factor from the optimal cost. Such a policy results from parameterized approximate value functions and the complexity of these functions determines the complexity of the policy. Typically, the more stringent the constant factor from the optimal cost is, the larger the complexity. However, relaxed dynamic programming does not give any guarantees on the complexity, which might still be unpractical. To tackle this issue, we propose to rather find the best factor away from optimality for a given complexity bound. We consider a large class of problems where the value functions can be represented as the minimum of quadratic functions. For this class, we propose a modified relaxed dynamic programming algorithm that ensures bounded complexity while still providing tight cost guarantees. A crucial step in the algorithm is the search for the best cost factor for a given policy with desired complexity, shown to be an optimization problem subject to Linear Matrix Inequalities (LMIs). We provide a new subclass of problems within this class and illustrate the effectiveness of our policy in a numerical instance of this subclass.

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A PREA and OODA Computing Framework of Unmanned systems to Perform Complex Tasks

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-18页

作者： Yang, Dongsheng Yu, Lei Zhang, Yi Zhu, Fenghua Li, Qiang Cui, Huachao Ma, Qiongmin Fan, Lili Tian, Yonglin Jinan University Guangzhou China Intelligent Science & Technology Academy Limited of CASIC Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 28th Research Institute of China Electronics Technology Group Corporation Nanjing China National Key Laboratory for Complex Systems Simulation National University of Defense Technology Changsha China School of Information and Electronics Beijing Institute of Technology Beijing China

A C2 computing framework for unmanned systems to perform complex tasks is proposed using methods of system of systems engineering, which is formed by combining the macro-scale command and control (C2) process mechanism model (PREA loop) and micro-scale C2 process mechanism model (OODA loop). Guided by PREA loop and OODA loop, the computing framework is divided into four steps and three kinds of transformations. The four steps are design, construction, operation monitoring, and assessment. The three transformations are tactical feedback, campaign feedback, and strategic feedback. A C2 organization model of joint landing combat force is established against the background of a typical complex task of joint landing operation, and the C2 computing framework based on the PREA &OODA is used to implement the C2 activities of the joint landing combat force. The influence of the computing framework on the performance of unmanned systems under different task conditions is verified, including task coordination load, task efficiency and sensitivity of unmanned systems response. Authors

关键词： Feedback

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Unconstrained Parameterization of Stable LPV Input-Output Models: with Application to System Identification

arXiv

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arXiv 2024年

作者： Kon, Johan van de Wijdeven, Jeroen Bruijnen, Dennis Tóth, Roland Heertjes, Marcel Oomen, Tom Control Systems Technology Group Departement of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands Philips Engineering Solutions Eindhoven Netherlands Control Systems Group Electrical Engineering Eindhoven University of Technology Netherlands The HUN-REN Institute for Computer Science and Control Budapest Hungary Delft University of Technology Delft Netherlands

Ensuring stability of discrete-time (DT) linear parameter-varying (LPV) input-output (IO) models estimated via system identification methods is a challenging problem as known stability constraints can only be numerically verified, e.g., through solving Linear Matrix Inequalities. In this paper, an unconstrained DT-LPV-IO parameterization is developed which gives a stable model for any choice of model parameters. To achieve this, it is shown that all quadratically stable DT-LPV-IO models can be generated by a mapping of transformed coefficient functions that are constrained to the unit ball, i.e., a small-gain condition. The unit ball is then reparameterized through a Cayley transformation, resulting in an unconstrained parameterization of all quadratically stable DT-LPV-IO models. As a special case, an unconstrained parameterization of all stable DT linear time-invariant transfer functions is obtained. Identification using the stable DT-LPV-IO model with neural network coefficient functions is demonstrated on a simulation example of a position-varying mass-damper-spring system. © 2024, CC BY-NC-ND.

关键词： Parameterization

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Unconstrained Parameterization of Stable LPV Input-Output Models: with Application to System Identification

Unconstrained Parameterization of Stable LPV Input-Output Mo...

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European control Conference (ECC)

作者： Johan Kon Jeroen Van De Wijdeven Dennis Bruijnen Roland Tóth Marcel Heertjes Tom Oomen Departement of Mechanical Engineering Control Systems Technology Group Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Philips Engineering Solutions Eindhoven The Netherlands Control Systems Group Electrical Engineering Eindhoven University of Technology The Netherlands HUN-REN Institute for Computer Science and Control Budapest Hungary Delft University of Technology Delft The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

关键词： Computational modeling Neural networks Riccati equations Transfer functions Mathematical models Stability analysis Numerical models

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Demonstration of the Dyna Reinforcement Learning Framework for Reactive Close Proximity Operations

Demonstration of the Dyna Reinforcement Learning Framework f...

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

作者： Majumdar, Ritwik Albee, Keenan Sternberg, David C. Jia-Richards, Oliver Department of Aerospace Engineering University of Michigan Ann ArborMI United States Payload/Instrument Pointing Control Systems Engineering Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Maritime and Multi-Agent Autonomy Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Lessons from the International Space Station (ISS) emphasize the necessity of exterior inspection for anomaly detection and maintenance, but current methods rely on costly and limited human extravehicular activities and robotic arms. Deployable free-flying small spacecraft offer a flexible, autonomous solution, capable of comprehensive exterior inspections without human involvement. However, the safety of these spacecraft during close proximity operations remains a concern, particularly given uncertain variability in thruster performance. This paper presents SmallSat Steward, a reactive and integrated architecture for online model learning and trajectory planning based on the Dyna reinforcement learning architecture. By combining model-based planning and direct reinforcement learning, Dyna offers a potentially flexible and computationally-efficient solution capable of adapting to changes in thruster performance and other system uncertainties. Preliminary results in both simulation and hardware environments demonstrate the potential of this architecture to successfully regulate position under single and double thruster failures. In simulation, the Dyna-based controller outperformed an PD-LQR controller in ∼70% of all cases. On hardware, Dyna was able to eliminate the steady state error caused by thruster failures. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Space stations

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Achievable Rates for Information Extraction from a Strategic Sender

arXiv

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arXiv 2023年

作者： Vora, Anuj S. Kulkarni, Ankur A. Delft Center for Systems and Control group Delft University of Technology Delft2628CD Netherlands Systems and Control Engineering group The Indian Institute of Technology Bombay Mumbai400076 India

We consider a setting of non-cooperative communication where a receiver wants to recover randomly generated sequences of symbols that are observed by a strategic sender. The sender aims to maximize an average utility that may not align with the recovery criterion of the receiver, whereby the signals it sends may not be truthful. The rate of communication is defined as the number of reconstructions corresponding to the sequences recovered correctly while communicating with the sender. We pose this problem as a sequential game between the sender and the receiver with the receiver as the leader and determine strategies for the receiver that attain vanishing probability of error and compute the rates of such strategies. We show the existence of such strategies under a condition on the utility of the sender. For the case of the binary alphabet, this condition is also necessary, in the absence of which, the probability of error goes to one for all choices of strategies of the receiver. We show that for reliable recovery, the receiver chooses to correctly decode only a subset of messages received from the sender and deliberately makes an error on messages outside this subset. Despite a clean channel, our setting exhibits a non-trivial maximum rate of communication, which is in general strictly less than the capacity of the channel. This implies the impossibility of strategies that correctly decode sequences of rate greater than the maximum rate while also achieving reliable communication. This is a key point of departure from the usual setting of cooperative communication. Copyright © 2023, The Authors. All rights reserved.

关键词： Recovery

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DC operating circuit anomaly detection based on node voltage unsupervised time series 2

DC operating circuit anomaly detection based on node voltage...

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2nd International Conference on New Energy and Power Engineering, ICNEPE 2022

作者： Zhang, Shen Qi Yuan, Wei Yi, Ran Chen, Li State Grid NanTongPower Supply Company Jiangsu NanTong226000 China NARI Technology Nanjing Control Systems Co. Ltd Jiangsu Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation Jiangsu Nanjing211106 China

With the increase in power system load, the number of switch cabinets increases rapidly, and the accidents caused by DC operating circuits become more and more obvious. Abnormal detection has become an important part of the DC operating circuit. Abnormal data, mainly voltage measurement, often contain important information. Finding and analyzing these abnormal data can give early warning for circuit failure or failure. However, abnormal data is often difficult to obtain and lacks marks, that is, the problem of sample imbalance and unsupervised problems, resulting in abnormal detection methods that can not meet the increasing accuracy and efficiency requirements. Generative adversarial network (GAN) is an unsupervised deep learning model, which has been successfully applied to unsupervised time series anomaly detection. However, GAN has technical difficulties in the anomaly detection process, and there is still room for optimization in accuracy. In this paper, the unsupervised time series anomaly detection method based on GAN is studied, and an anomaly detection method of a DC operating circuit combined with LSTM and GAN is designed. © Published under licence by IOP Publishing Ltd.

关键词： Generative adversarial networks

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Rejecting an Unknown Matched Disturbance from an Infinite-Dimensional control System

Rejecting an Unknown Matched Disturbance from an Infinite-Di...

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IEEE Conference on Decision and control

作者： Bhagyashri Gurjar Bhargav Pavan Kumar Sistla Vivek Natarajan Systems and Control Engineering Group Indian Institute of Technology Bombay Mumbai India

In this paper we address the problem of rejecting an unknown disturbance, which is matched with the input, from an infinite-dimensional plant belonging to the class of regular linear systems. The plant input and output are finite-dimensional and the time-derivative of the disturbance is assumed to be bounded with a known bound. In our solution approach to this problem, we drive a stable ODE using the output of the plant. Via a state transformation obtained by solving a Sylvester equation with possibly unbounded operators, we derive an auxiliary ODE in which the disturbance and the input are matched. We then build a nonlinear disturbance observer for the auxiliary ODE, based on the super-twisting sliding mode algorithm, to generate asymptotically accurate estimates for the unknown disturbance. By letting the input to the plant to be the negative of the disturbance estimate obtained, the matched disturbance in the plant can be rejected. In case the plant is unstable, including a stabilizing feedback signal in the input will ensure that the plant state converges to zero asymptotically. Our approach requires the state of the plant to be known. When only the plant output is known, our approach can be implemented using a state observer for the plant and then modifying the disturbance observer suitably. We demonstrate the efficacy of our approach in simulations by taking the plant to be an anti-stable 1D wave equation and assuming output measurement.

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