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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Wang, Ming Zhang, Yanlu Dong, Huifang Li, Xu Yu, Junzhi Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan250100 China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538660720

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system. © 2018 IEEE.

关键词： controllers

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Design of Gain Scheduled control in Frequency Domain

Design of Gain Scheduled Control in Frequency Domain

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International Conference on Process control

作者： Vojtech Vesely Jakub Osusky Peter Guzmicky Institute of Control and Industrial Informatics Faculty of Electrical Engineering and Information Technology in Bratislava

ISBN: (纸本)9781479909261

This paper presents gain scheduled controller design for MIMO systems in frequency domain. Stability conditions, based on characteristic equation, are obtained using small gain theory. Proposed method is based on M-delta structure and numerical example is included for effectiveness illustration. In the example for decentralized controller design equivalent subsystem method is used.

关键词： Gain scheduled control Small gain theorem Frequency domain PI controller

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A tracking control synthesis for uncertain delay nonlinear systems based on T-S fuzzy model

A tracking control synthesis for uncertain delay nonlinear s...

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2012 6th IEEE International Conference Intelligent Systems, IS 2012

作者： Stojanovski, Goran Nadzinski, Gorjan Stankovski, Mile Jiang, Xin-Wei Faculty of Electrical Eng. and Information Technologies Institute for ASE SS Cyril and Methodius University Skopje MK-1000 Macedonia College of Information Science and Engineering Institute of Control Theory and Navigation Technology Northeastern University Shenyang Liaoning 100006 China

ISBN: (纸本)9781467327824

A novel robust tracking control technique for time-delay systems with uncertain time-delays based on fuzzy T-S is presented. Fuzzy T-S model with parametric uncertainties is employed to represent the uncertain time-delay plant. This control synthesis design is shown reduce the tracking error considerably for all bounded reference inputs while guaranteeing the H performance. The proposed solution has advantage of employing only a simple fuzzy controller and no complicated adaptive scheme. The fuzzy tracking control synthesis is parameterized in terms of a linear matrix inequality, which are solved efficiently by using convex optimization techniques. This method has been applied to trailer-truck example and respective numerical and simulation results demonstrate its valid applicability and efficiency. © 2012 IEEE.

关键词： Linear matrix inequalities

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Deep Reinforcement Learning-Based Path-Tracking for Unmanned Vehicle Navigation Enhancement

Deep Reinforcement Learning-Based Path-Tracking for Unmanned...

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2024 International Conference on Electronics, information, and Communication, ICEIC 2024

作者： Yang, Seung Geon Cho, Eun Ho Kim, Jeongyun Lim, Seung-Chan School of ICT Robotics and Mechanical Engineering Hankyong National University Anseong Korea Republic of School of Electrical Electronic and Control Engineering Hankyong National University Anseong Korea Republic of Massachusetts Institute of Technology Wireless Information and Network Sciences Laboratory CambridgeMA02139 United States

ISBN: (纸本)9798350371888

Despite the growing interest in autonomous vehicles, practical challenges remain particularly in achieving high tracking performance. In this study, we address this issue by developing a path tracking algorithm based on deep reinforcement learning. To this end, we elaborately design the Markov decision process and implement the deep Q-network (DQN) training algorithm. Simulation results validate the superior convergence speed, accuracy, and stability of the proposed DQN-based tracking algorithm in comparison to the conventional approach. © 2024 IEEE.

关键词： Reinforcement learning

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Repetitive process control theory applied to the modeling and control of ladder circuits ?

Repetitive process control theory applied to the modeling an...

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11th IFAC International Workshop on Adaptation and Learning in control and Signal Processing, ALCOSP 2013

作者： Sulikowski, Bartlomiej Galkowski, Krzysztof Kummert, Anton Rogers, Eric Institute of Control and Computation Engineering University of Zielona Gora Poland Faculty of Electrical Information and Media Engineering University of Wuppertal Germany Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom

ISBN: (纸本)9783902823373

Repetitive processes propagate information in two separate directions, one of which is temporal and the other can be spatial. A repetitive process makes a series of sweeps, or passes, through a set of dynamics over this finite duration and when each is complete the process resets. Moreover, the output produced on the previous pass explicitly contributes to the dynamics produced on the next one. Hence they can also be viewed as a class of periodic systems. They also pose control problems that cannot be solved by standard systems control theory and design algorithms. This paper gives new results on the application of the repetitive process control theory to the analysis of ladder networks. © IFAC.

关键词： control theory

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Composite systems control by combined math-analytical and FS/NN computing approach 3

Composite systems control by combined math-analytical and FS...

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3rd IFAC Workshop on Automatic Systems for Building the Infrastructure in Developing Countries, DECOM-TT 2003

作者： Dimirovski, Georgi M. Jing, Yuan-Wei Zhao, Jun Zhang, Si-Ying Dogus University Department of Computer Engineering Faculty of Engineering Acibadem Kadiköy IstanbulTR-34722 Turkey SS Cyril and Methodius University Institute of Automation and Systems Eng Faculty of Electrical Engineering SkopjeMK-1000 Macedonia Northeastern University Institute of Control Science School of Information Science and Eng. Shenyang Liaoning China

A control systems engineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detail. One design alternative is based on employing fuzzy-system approximators and solving for the adaptive tracking of the given, arbitrary, desired system outputs. The other alternative is based on state equations of composite systems and the use of neural-network approximators to deal with uncertainties and control adaptation. In both alternatives similarity property of subsystems has been exploited. Both designs can be implemented within the standard computer process control technology, and are therefore believed to be promising in applied systems engineering. Copyright © 2003 IFAC.

关键词： Fuzzy systems

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Robust Gain-Scheduled controller Design for T1DM Individualised Model

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IFAC-PapersOnLine 2015年第14期48卷 82-87页

作者： Adrian Ilka Tomas Ludwig Ivan Ottinger Marián Tárník Eva Miklovicová Vojtech Veselá Ján Murgas Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Ilkovicova 3 812 19 Bratislava

Novel original robust gain-scheduled controller design for individualized type 1 diabetes mellitus (T1DM) subject model is presented in this paper. For controller design an LPV model is created from insulin-glucose subsystem based on Bergman’s minimal model with subcutaneous insulin absorption and absorption of digested carbohydrates. Identification was performed on pharmacokinetics and pharmacodynamics characteristics of administered insulin and data collected from continuous glucose monitoring (CGM) system. The controller design approach guarantees the closed-loop stability and cost for all scheduled parameter changes. Simulation results show the benefits of the proposed approach.

关键词： LPV system Robust controller Gain-scheduling Output feedback Quadratic stability Type 1 diabetes mellitus model

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MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions, spherical coordinates, and intensity

arXiv

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arXiv 2021年

作者： Zywanowski, Kamil Banaszczyk, Adam Nowicki, Michal R. Komorowski, Jacek Institute of Robotics and Machine Intelligence Faculty of Control Robotics and Electrical Engineering Poznan University of Technology Poznan Poland Faculty of Electronics and Information Technology Warsaw University of Technology Warsaw Poland

The 3D LiDAR place recognition aims to estimate a coarse localization in a previously seen environment based on a single scan from a rotating 3D LiDAR sensor. The existing solutions to this problem include hand-crafted point cloud descriptors (e.g., ScanContext, M2DP, LiDAR IRIS) and deep learning-based solutions (e.g., PointNetVLAD, PCAN, LPD-Net, DAGC, MinkLoc3D), which are often only evaluated on accumulated 2D scans from the Oxford RobotCar dataset. We introduce MinkLoc3D-SI, a sparse convolution-based solution that utilizes spherical coordinates of 3D points and processes the intensity of 3D LiDAR measurements, improving the performance when a single 3D LiDAR scan is used. Our method integrates the improvements typical for hand-crafted descriptors (like ScanContext) with the most efficient 3D sparse convolutions (MinkLoc3D). Our experiments show improved results on single scans from 3D LiDARs (USyd Campus dataset) and great generalization ability (KITTI dataset). Using intensity information on accumulated 2D scans (RobotCar Intensity dataset) improves the performance, even though spherical representation doesn’t produce a noticeable improvement. As a result, MinkLoc3D-SI is suited for single scans obtained from a 3D LiDAR, making it applicable in autonomous vehicles. © 2021, CC BY-SA.

关键词： Convolution

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Structured coprime factorizations description of linear and time-invariant networks

Structured coprime factorizations description of linear and ...

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52nd IEEE Conference on Decision and control, CDC 2013

作者： SabǍu, Şerban OarǍ, Cristian Warnick, Sean Jadbabaie, Ali Electrical and Computer Engineering Dept. Stevens Institute of Technology United States Faculty of Automatic Control Dept. University Politehnica Bucharest Romania Faculty of Computer Science Department Information and Decision Algorithms Laboratories Brigham Young University United States Faculty of Electrical and Systems Engineering Dept. University of Pennsylvannia United States

ISBN: (纸本)9781467357173

In this paper we study state-space realizations of Linear and Time-Invariant (LTI) systems. Motivated by biochemical reaction networks, Gonçalves and Warnick have recently introduced the notion of a Dynamical Structure Functions (DSF), a particular factorization of the system's transfer function matrix that elucidates the interconnection structure in dependencies between manifest variables. We build onto this work by showing an intrinsic connection between a DSF and certain sparse left coprime factorizations. By establishing this link, we provide an interesting systems theoretic interpretation of sparsity patterns of coprime factors. In particular we show how the sparsity of these coprime factors allows for a given LTI system to be implemented as a network of LTI sub-systems. We examine possible applications in distributed control such as the design of a LTI controller that can be implemented over a network with a pre-specified topology. ©2013 IEEE.

关键词： Factorization

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Recent Advances in Model Predictive control 1

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丛书名： Lecture Notes in control and information Sciences

1000年

作者： Timm Faulwasser Matthias A. Müller Karl Worthmann

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