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Data-Driven quasi-LPV Model Predictive control Using Koopman Operator Techniques

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IFAC-PapersOnLine 2020年第2期53卷 6062-6068页

作者： Pablo. S.G. Cisneros Adwait Datar Patrick Göttsch Herbert Werner Institute of Control Systems Hamburg University of Technology Germany

A fast data-driven extension of the velocity-based quasi-linear parameter-varying model predictive control (qLMPC) approach is proposed for scenarios where first principles models are not available or are computationally too expensive. We use tools from the recently proposed Koopman operator framework to identify a quasi-linear parameter-varying model (in input/output and state-space form) by choosing the observables from physical insight. An online update strategy to adapt to changes in the plant dynamics is also proposed. The approach is validated experimentally on a strongly nonlinear 3-degree-of-freedom control Moment Gyroscope, showing remarkable tracking performance.

关键词： Nonlinear predictive control linear parameter-varying systems data-driven control Koopman operator adaptive control

A Unified Approach to Evaluation and Routing in Public Transport systems

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arXiv 2022年

作者： van Lieshout, Rolf N. Dalmeijer, Kevin Department of Operations Planning Accounting and Control School of Industrial Engineering Eindhoven University of Technology Netherlands H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology United States

Both evaluating the service quality of a public transport system and understanding how passengers choose between modes or routes is imperative for public transport operators, providers of competing mobility services and policy makers. However, the literature does not offer consensus on how either of these tasks should be performed, which can lead to inconsistent or counter-intuitive results. This paper provides a formal treatment on how common manifestations of public transport (route sets, timetables and line plans) can be evaluated consistently, and how passengers distribute over routes. Our main insight is that evaluation and routing are two sides of the same coin: by solving an appropriate optimization model one obtains both the quality of the route set, timetable or line plan (the optimal objective value), and the distribution of the travelers over the routes (the optimal solution itself). We further demonstrate that the framework developed in this paper enables planners to (i) improve service by taking better decisions and (ii) assess to what degree of accuracy traveler behavior should be modeled on their network, potentially avoiding investing in complicated methods that may not be necessary. Copyright © 2022, The Authors. All rights reserved.

关键词： Transportation routes

Predictive Synthesis of control Barrier Functions and its Application to Time-Varying Constraints

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arXiv 2025年

作者： Wiltz, Adrian Dimarogonas, Dimos V. Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

This paper presents a systematic method for synthesizing a control Barrier Function (CBF) that encodes predictive information into a CBF. Unlike other methods, the synthesized CBF can account for changes and time-variations in the constraints even when constructed for time-invariant constraints. This avoids recomputing the CBF when the constraint specifications change. The method provides an explicit characterization of the extended class Ke function α that determines the dynamic properties of the CBF, and α can even be explicitly chosen as a design parameter in the controller synthesis. The resulting CBF further accounts for input constraints, and its values can be determined at any point without having to compute the CBF over the entire domain. The synthesis method is based on a finite horizon optimal control problem inspired by Hamilton-Jacobi reachability analysis and does not rely on a nominal control law. The synthesized CBF is time-invariant if the constraints are. The method poses mild assumptions on the controllability of the dynamic system and assumes the knowledge of at least a subset of some control invariant set. The paper provides a detailed analysis of the properties of the synthesized CBF, including its application to time-varying constraints. A simulation study applies the proposed approach to various dynamic systems in the presence of time-varying constraints. The paper is accompanied by an online available parallelized implementation of the proposed synthesis method. Copyright © 2025, The Authors. All rights reserved.

关键词： Invariance

Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

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Computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

Quantum state and detector tomography with known rank

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IFAC-PapersOnLine 2023年第2期56卷 5881-5887页

作者： Shuixin Xiao Yuanlong Wang Jun Zhang Daoyi Dong Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia University of Michigan - Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China Centre for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia

Quantum state tomography and quantum detector tomography are two main problems in quantum system identification. In this paper, we study state tomography and detector tomography with prior knowledge about the true rank of the unknown state/detector. In this case, we propose a sufficient condition for static (non-adaptive) tomography algorithms to achieve the optimal infidelity scaling O(1/N) on the number of state copies N. Then we present two examples of such static quantum state tomography and quantum detector tomography algorithms. Numerical examples demonstrate the effectiveness of our algorithms.

关键词： Quantum system identification quantum state tomography quantum detector tomography

Scheduling and control over networks using MPC with time-varying terminal ingredients

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Scheduling and control over networks using MPC with time-var...

American control Conference

作者： Stefan Wildhagen Frank Allgower Institute for Systems Theory and Automatic Control University of Stuttgart Germany

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Rollout approaches are an effective tool to address the problem of co-designing the transmission schedule and the corresponding input values, when the controller is connected to the plant via a resource-constrained communication network. These approaches typically employ an MPC, activated at multiples of the period length of a base transmission schedule. Using multi-step invariant terminal regions and a prediction horizon longer than the base period, stability can be ensured. This strategy, however, suffers from intrinsic shortcomings, such as a high computational complexity and low robustness. We aim to resolve these drawbacks by proposing an MPC with periodically time-varying terminal region and cost for the rollout setup, where the controller is activated at each time instant and features an arbitrary but fixed prediction horizon. We consider in more detail two specific setups from the literature on Networked control systems, namely the token bucket network and actuator scheduling. For both setups, we provide conditions for which convergence under application of the time-varying MPC can be guaranteed. In a numerical example, we demonstrate the benefits of the proposed method.

关键词： duration of menstrual flow time varying controllers application time networks(communications) complexity classes Network numerical example

Distributed Optimization for Quadratic Cost Functions over Large-Scale Networks with Quantized Communication and Finite-Time Convergence

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arXiv 2023年

作者： Rikos, Apostolos I. Grammenos, Andreas Kalyvianaki, Evangelia Hadjicostis, Christoforos N. Charalambous, Themistoklis Johansson, Karl H. The Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden The Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom The Alan Turing Institute London United Kingdom The Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia1678 Cyprus

We propose two distributed iterative algorithms that can be used to solve, in finite time, the distributed optimization problem over quadratic local cost functions in large-scale networks. The first algorithm exhibits synchronous operation whereas the second one exhibits asynchronous operation. Both algorithms share salient features. Specifically, the algorithms operate exclusively with quantized values, which means that the information stored, processed and exchanged between neighboring nodes is subject to deterministic uniform quantization. The algorithms rely on event-driven updates in order to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage. Finally, once the algorithms converge, nodes distributively terminate their operation. We prove that our algorithms converge in a finite number of iterations to the exact optimal solution depending on the quantization level, and we present applications of our algorithms to (i) optimal task scheduling for data centers, and (ii) global model aggregation for distributed federated learning. We provide simulations of these applications to illustrate the operation, performance, and advantages of the proposed algorithms. Additionally, it is shown that our proposed algorithms compare favorably to algorithms in the current literature. Quantized communication and asynchronous updates increase the required time to completion, but finite-time operation is maintained. © 2023, CC BY.

关键词： Cost functions

Training robust neural networks using Lipschitz bounds

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arXiv 2020年

作者： Pauli, Patricia Koch, Anne Berberich, Julian Kohler, Paul Allgöwer, Frank The Institute for Systems Theory and Automatic Control University of Stuttgart Germany

Due to their susceptibility to adversarial perturbations, neural networks (NNs) are hardly used in safety-critical applications. One measure of robustness to such perturbations in the input is the Lipschitz constant of the input-output map defined by an NN. In this work, we propose a framework to train multi-layer NNs while at the same time encouraging robustness by keeping their Lipschitz constant small, thus addressing the robustness issue. More specifically, we design an optimization scheme based on the Alternating Direction Method of Multipliers that minimizes not only the training loss of an NN but also its Lipschitz constant resulting in a semidefinite programming based training procedure that promotes robustness. We design two versions of this training procedure. The first one includes a regularizer that penalizes an accurate upper bound on the Lipschitz constant. The second one allows to enforce a desired Lipschitz bound on the NN at all times during training. Finally, we provide two examples to show that the proposed framework successfully increases the robustness of NNs. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

Performance Analysis of Distributed Filtering under Mismatched Noise Covariances

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arXiv 2024年

作者： Lyu, Xiaoxu Wen, Guanghui Shi, Ling Duan, Peihu Duan, Zhisheng The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The Laboratory of Security Operation and Control for Intelligent Autonomous Systems Department of Systems Science School of Mathematics Southeast University Nanjing211189 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation indices for such filtering problems, namely the standard performance evaluation index, the nominal performance evaluation index, and the estimation error covariance. We derive difference expressions among these indices and establish one-step relations among them under various mismatched noise covariance scenarios. We particularly reveal the effect of the consensus fusion on these relations. Furthermore, the recursive relations are introduced by extending the results of the one-step relations. Subsequently, we demonstrate the convergence of these indices under the collective observability condition, and show this convergence condition of the nominal performance evaluation index can guarantee the convergence of the estimation error covariance. Additionally, we prove that the estimation error covariance of the consensus-based distributed filter under mismatched noise covariances can be bounded by the Frobenius norms of the noise covariance deviations and the trace of the nominal performance evaluation index. Finally, the effectiveness of the theoretical results is verified by numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Wiener filtering