检索结果-内蒙古大学图书馆

Deep Subspace Encoders for Nonlinear System Identification

学校读者我要写书评

暂无评论

arXiv 2022年

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

Using Artificial Neural Networks (ANN) for nonlinear system identification has proven to be a promising approach, but despite of all recent research efforts, many practical and theoretical problems still remain open. Specifically, noise handling and models, issues of consistency and reliable estimation under minimisation of the prediction error are the most severe problems. The latter comes with numerous practical challenges such as explosion of the computational cost in terms of the number of data samples and the occurrence of instabilities during optimization. In this paper, we aim to overcome these issues by proposing a method which uses a truncated prediction loss and a subspace encoder for state estimation. The truncated prediction loss is computed by selecting multiple truncated subsections from the time series and computing the average prediction loss. To obtain a computationally efficient estimation method that minimizes the truncated prediction loss, a subspace encoder represented by an artificial neural network is introduced. This encoder aims to approximate the state reconstructability map of the estimated model to provide an initial state for each truncated subsection given past inputs and outputs. By theoretical analysis, we show that, under mild conditions, the proposed method is locally consistent, increases optimization stability, and achieves increased data efficiency by allowing for overlap between the subsections. Lastly, we provide practical insights and user guidelines employing a numerical example and state-of-the-art benchmark results. © 2022, CC BY.

关键词： Forecasting

Funnel control Under Hard and Soft Output Constraints (extended version)

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Mehdifar, Farhad Bechlioulis, Charalampos P. Dimarogonas, Dimos V. The Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden The Division of Systems and Control The Department of Electrical and Computer Engineering University of Patras Patra Greece

This paper proposes a funnel control method under time-varying hard and soft output constraints. First, an online funnel planning scheme is designed that generates a constraint consistent funnel, which always respects hard (safety) constraints, and soft (performance) constraints are met only when they are not conflicting with the hard constraints. Next, the prescribed performance control method is employed for designing a robust low-complexity funnel-based controller for uncertain nonlinear Euler-Lagrangian systems such that the outputs always remain within the planned constraint consistent funnels. Finally, the results are verified with a simulation example of a mobile robot tracking a moving object while staying in a box-constrained safe space. Copyright © 2022, The Authors. All rights reserved.

关键词：

Fuzzy System of Wind Turbine Defect Image Processing

学校读者我要写书评

暂无评论

Fuzzy System of Wind Turbine Defect Image Processing

International Conference on Advanced computer Information Technologies (ACIT)

作者： Lesia Dubchak Anatoliy Sachenko Carsten Wolff Nadia Vasylkiv Department of Computer Engineerin West Ukrainian National University Ternopil Ukraine Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Tele-Informatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland Dortmund University of Applied Science and Arts Dortmund Germany Department of Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

Wind turbines are an important component of the global strategy for the transition to renewable energy sources and the fight against climate change. Their implementation contributes to sustainable development and to improving the ecological situation of the planet. Detecting and elimination of defects helps reduce the wear of the components and prevent premature failure. This can significantly extend the life of wind turbines, which is economically beneficial for owners and operators. The use of UAVs allows for minimizing the risks for personnel, as inspection and diagnosis of defects can be carried out without the need to lift people to great heights or stay in dangerous areas. This is especially important for turbines located in places of difficult access. The images taken by the UAV contain many extraneous objects and fuzzy data. Fuzzy logic allows you to create models for pattern recognition and object classification in images, taking into account uncertainty and variation in the data. This increases the accuracy and reliability of pattern recognition systems. This article proposes an image processing system to detect wind turbine defects, with a fuzzy system module that selects images from a video stream for further processing.

关键词： Fuzzy logic Renewable energy sources Costs Accuracy Uncertainty Image processing Streaming media Wind turbines Pattern recognition Fuzzy systems

Enhanced LPV-based lateral control using ultra-local model-based slip angle estimation

学校读者我要写书评

暂无评论

Enhanced LPV-based lateral control using ultra-local model-b...

IEEE Conference on Decision and control

作者： Dániel Fényes Tamás Hegedűs Péter Gáspár Hungarian Research Network (HUN-REN) Kende u. 13-17 Institute for Computer Science and Control (SZTAKI) Budapest Hungary Department for Control of Transportation and Vehicle Systems Budapest University of Technology and Economics Stoczek u 2 Budapest Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The paper presents a combined observer and lateral control design approach for autonomous vehicles. The goal of the observer design is to estimate the front and rear slip angles of the vehicle together with the cornering stiffness. The observer is based on the combination of the polytopic LPV approach and the ultra-local model. The ultra-local model is used to update the cornering stiffness and, in this way, improve the performance level of the LPV observer. Then, the resulted observer is exploited during the LPV-based lateral control design. The improved lateral control can adapt to different circumstances such as low adhesion coefficient. The proposed observer and LPV controller is implemented and tested in MATLAB/Simulink environment and using the high-fidelity simulation software, CarMaker.

关键词： Adaptation models control design Heuristic algorithms Software algorithms Estimation Observers Mathematical models Software MATLAB Autonomous vehicles

Optimized Ensemble Algorithm for Predicting Metamaterial Antenna Parameters

学校读者我要写书评

暂无评论

computers, Materials & Continua 2022年第6期71卷 4989-5003页

作者： El-Sayed M.El-kenawy Abdelhameed Ibrahim Seyedali Mirjalili Yu-Dong Zhang Shaima Elnazer Rokaia M.Zaki Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Nile Higher Institute for Engineering and Technology MansouraEgypt Computer and Information Technology College Taif UniversityTaifSaudi Arabia Higher Institute of Engineering and Technology Kafrelsheikh Department of Electrical Engineering Shoubra Faculty of EngineeringBenha UniversityEgypt

Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve *** antennas can overcome the bandwidth constraint associated with tiny *** learning is receiving a lot of interest in optimizing solutions in a variety of *** learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today’s *** accuracy of the forecast is mostly determined by the model *** purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the Metamaterial *** Vector Machines(SVM),Random Forest,K-Neighbors Regressor,and Decision Tree Regressor were utilized as the basic *** Adaptive Dynamic Polar Rose Guided Whale Optimization method,named AD-PRS-Guided WOA,was used to pick the optimal features from the *** suggested model is compared to models based on five variables and to the average ensemble *** findings indicate that the presented model using Random Forest results in a Root Mean Squared Error(RMSE)of(0.0102)for bandwidth and RMSE of(0.0891)for *** is superior to other models and can accurately predict antenna bandwidth and gain.

关键词： Metamaterial antenna machine learning ensemble model feature selection guided whale optimization support vector machines

Classification of Wind Turbine Defects based on the SqueezeNet Neural Network

学校读者我要写书评

暂无评论

Classification of Wind Turbine Defects based on the SqueezeN...

International computer Sciences and Information Technologies (CSIT)

作者： Lesia Dubchak Anatoliy Sachenko Carsten Wolff Nadiia Vasylkiv Zenovii Bernas Department of Computer Engineering West Ukrainian National University Ternopil Ukraine Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Tele-Informatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland Dortmund University of Applied Science and Arts Dortmund Germany Department of Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

The article presents a study on classifying wind turbine defects using the SqueezeNet neural network. Wind turbines are critical for renewable energy, but defects such as corrosion, erosion, and cracks can significantly reduce their efficiency. The study proposes using image classification techniques with neural networks, particularly SqueezeNet, to automate defect detection. The compact nature of SqueezeNet makes it suitable for real-time applications with limited computing resources. Through training and testing, the network achieved an accuracy of 89%, demonstrating its potential to improve wind turbine maintenance and reduce operational costs.

关键词： Training Accuracy Costs Neural networks Real-time systems Wind turbines Maintenance Defect detection Testing Image classification

Observer-Based control of Second-Order Multi-vehicle systems in Bearing-Persistently Exciting Formations

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Tang, Zhiqi Fidan, Baris Johansson, Karl H. Mårtensson, Jonas Hamel, Tarek Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden Mechanical and Mechatronics Engineering Department University of Waterloo ON Canada France

This paper proposes an observer-based formation tracking control approach for multi-vehicle systems with second-order motion dynamics, assuming that vehicles' relative or global position and velocity measurements are unavailable. It is assumed that all vehicles are equipped with sensors capable of sensing the bearings relative to neighboring vehicles and only one leader vehicle has access to its global position. Each vehicle estimates its absolute position and velocity using relative bearing measurements and the estimates of neighboring vehicles received over a communication network. A distributed observer-based controller is designed, relying only on bearing and acceleration measurements. This work further explores the concept of the Bearing Persistently Exciting (BPE) formation by proposing new algorithms for bearing-based localization and state estimation of second-order systems in centralized and decentralized manners. It also examines conditions on the desired formation to guarantee the exponential stability of distributed observer-based formation tracking controllers. In support of our theoretical results, some simulation results are presented to illustrate the performance of the proposed observers as well as the observer-based tracking controllers. © 2024, CC BY-NC-ND.

关键词： Acceleration measurement

Distributed Prescribed-Time Observer for Nonlinear systems in Block-Triangular Form

学校读者我要写书评

暂无评论

arXiv 2025年

作者： de Heij, Vincent Niazi, M.B. Umar Johansson, Karl H. Ahmed, Saeed Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

This paper proposes a distributed prescribed-time observer for nonlinear systems representable in a block-triangular observable canonical form. Using a weighted average of neighbor estimates exchanged over a strongly connected digraph, each observer estimates the system state despite the limited observability of local sensor measurements. The proposed design guarantees that distributed state estimation errors converge to zero at a user-specified convergence time, irrespective of observers’ initial conditions. To achieve this prescribed-time convergence, distributed observers implement time-varying local output injection gains that monotonically increase and approach infinity at the prescribed time. The theoretical convergence is rigorously proven and validated through numerical simulations, where some implementation issues due to increasing gains have also been clarified. Copyright © 2025, The Authors. All rights reserved.

关键词： Digital arithmetic

Non-Convex Potential Games for Finding Global Solutions to Sensor Network Localization

学校读者我要写书评

暂无评论

Non-Convex Potential Games for Finding Global Solutions to S...

European control Conference (ECC)

作者： Gehui Xu Guanpu Chen Yiguang Hong Baris Fidan Thomas Parisini Karl H. Johansson Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Electronic Engineering Imperial College London London UK Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results.

关键词： Location awareness Coordinate measuring machines Simulation Current measurement Noise Europe Games