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8th International Conference on instrumentation, control, and Automation, ICA 2023

作者： Fathurrahman, Muhammad Farhan Catteeuw, Arne Gautama, Sidharta Aguirre, Angel L. Joelianto, Endra Sutarto, Herman Y. Ghent University Engineering and Product Design Department of Industrial Systems Ghent Belgium Department of Intelligent System Bandung Indonesia FlandersMake@UGent-Corelab ISyE Lommel Belgium Institut Teknologi Bandung Instrumentation and Control Research Group Faculty of Industrial Technology Bandung Indonesia

ISBN: (纸本)9798350301274

As the number of vehicles continues to increase every year, it is crucial to monitor traffic conditions effectively. Traffic forecasting serves as a valuable method in traffic management to support decision making. This study investigates the impact of utilizing spatio-Temporal data for traffic flow forecasting, as opposed to forecasting each location individually. We compare spatio-Temporal Long Short-Term Memory (LSTM), a machine-learning technique that utilizes spatially correlated sensor data in a network, and compare this to conventional LSTM and Seasonal ARIMA (SARIMA). Experiments have been conducted on counting loop data of a highway network in Belgium. We have investigated the performances of the forecasting model for different prediction horizons. The results show that spatial information improves the performance of the forecasting model and reduces the training time required. Further analysis show that the spatio-Temporal LSTM improves majorities of detectors while the minorities detectors are degraded which imply the importances of network selection. The computational load of the spatio-Temporal LSTM model is minimally impacted by the number of sensors in the network thus making it scalable. The results show that longer prediction horizons degrade the forecasting performance but the impact up to a 12 hour-horizon is not significant. © 2023 IEEE.

关键词： Long short-term memory

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Real-life Implementation and Comparison of Authenticated Path Following for Automated Vehicles based on Galileo OSNMA Localization

Real-life Implementation and Comparison of Authenticated Pat...

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Automated Vehicle Validation Conference (IAVVC), IEEE International

作者： Selim Solmaz Georg Nestlinger Karl Diengsleder-Lambauer Roman Lesjak Susanne Schweitzer José M. Vallet García (Dept.-E) Virtual Vehicle Research GmbH Graz Control Systems Group Austria (Dept.-E) Virtual Vehicle Research GmbH Graz Embedded Systems Group Austria Joanneum Research Forschungs GmbH Graz Austria Finnish Geospatial Research Institute Espoo Finland

We present a comparative analysis of EGNSS-based path tracking with and without open service navigation message authentication (OSNMA), which was recently made available in mass market EGNSS (Galileo) receivers. The EGNSS receivers provide dual-band GPS L1/L2 and Galileo E1/E5a RTK positioning for cm-level GNSS localization. The path following task utilizes mainly the accurate RTK-assisted EGNSS position and heading information to track a reference path. The lateral error from the reference path is used as the correction signal for the tracking controller. We compare the performance of the tracking controller in an open-sky and urban setting within the Graz University of Technology Inffeldgasse campus using an automated driving demonstrator vehicle. The positioning utilized two different OSNMA schemes, namely “strict” OSNMA solution that utilize only authenticated Galileo satellites or not using authentication, implying utilisation of all the available GNSS satellites.

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Semi/Fully-Automated Segmentation of Gastric-Polyp Using Aquila-Optimization-Algorithm Enhanced Images

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Computers, Materials & Continua 2022年第2期70卷 4087-4105页

作者： Venkatesan Rajinikanth Shabnam Mohamed Aslam Seifedine Kadry Orawit Thinnukool Department of Electronics and Instrumentation Engineering St.Joseph’s College of Engineering Chennai600119India Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Faculty of Applied Computing and Technology Noroff University CollegeKristiansand4608Norway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

The incident rate of the Gastrointestinal-Disease(GD)in humans is gradually rising due to a variety of reasons and the Endoscopic/Colonoscopic-Image(EI/CI)supported evaluation of the GD is an approved *** and evaluation of the suspicious section of the EI/CI is essential to diagnose the disease and its *** proposed research aims to implement a joint thresholding and segmentation framework to extract the Gastric-Polyp(GP)with better *** proposed GP detection system consist;(i)Enhancement of GP region using Aquila-Optimization-Algorithm supported tri-level thresholding with entropy(Fuzzy/Shannon/Kapur)and between-class-variance(Otsu)technique,(ii)Automated(Watershed/Markov-Random-Field)and semi-automated(Chan-Vese/Level-Set/Active-Contour)segmentation of GPfragment,and(iii)Performance evaluation and validation of the proposed *** experimental investigation was performed using four benchmark EI dataset(CVC-ClinicDB,ETIS-Larib,EndoCV2020 and Kvasir).The similarity measures,such as Jaccard,Dice,accuracy,precision,sensitivity and specificity are computed to confirm the clinical significance of the proposed *** outcome of this research confirms that the fuzzyentropy thresholding combined with Chan-Vese helps to achieve a better similarity measures compared to the alternative schemes considered in this research.

关键词： Endoscopic/colonoscopic-image gastric polyp aquila-optimizationalgorithm fuzzy entropy chan-vese segmentation

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The Regulation of a Quadrotor UAV Carrying a Pendulum using Receding Horizon control 12

The Regulation of a Quadrotor UAV Carrying a Pendulum using ...

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12th International Conference on Information Technology and Electrical Engineering, ICITEE 2020

作者： Tamba, Tua A. Nazaruddin, Yul Y. Juliastuti, Endang Parahyangan Catholic University Center for Control Automation Systems Engineering Department of Electrical Engineering Bandung Indonesia Institut Teknologi Bandung Instrumentation Control Research Group Indonesia

ISBN: (纸本)9781728110974

This paper proposes an approach for regulating the stability of an inverted pendulum that is attached on top of a moving quadrotor UAV. The approach is based on the receding horizon control scheme whose objective is to stabilize the pendulum in a vertical position while the quadrotor UAV is moving from predetermined initial to final poses. More specifically, the approach formulates a parametric quadratic optimization of the simultaneous stabilization of both the inverted pendulum and the quadrotor UAV. Simulation results are presented to demonstrate the successful implementation of the proposed method. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Polynomial-Based Linear Programming Relaxation of Sensor Network Localization Problem 12

Polynomial-Based Linear Programming Relaxation of Sensor Net...

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12th International Conference on Information Technology and Electrical Engineering, ICITEE 2020

作者： Tamba, Tua A. Nazaruddin, Yul Y. Parahyangan Catholic University Center for Control Automation Systems Engineering Department of Electrical Engineering Bandung Indonesia Institut Teknologi Bandung Instrumentation Control Research Group Indonesia

ISBN: (纸本)9781728110974

One important task in the deployment of a wireless sensor network is solving the sensor network localization problem to assure location awareness of each sensor node in the network. The sensor network localization can be formulated as a global optimization problem that aims to minimize the squared inter-sensor distances under the constraint that such distances equal to some given numbers. The corresponding optimization formulation is generally nonsmooth, nonconvex, and NP-hard problem, and thus prior works have proposed approximate solution using relaxation methods such as semidefinite or conic programming. In this paper, a linear programming relaxation approach is proposed to solve such an optimization problem using the concept of Handelman's representation of nonnegative polynomial functions over polytopic set. Numerical simulation results are given to illustrate the promising potential of the proposed approach. © 2020 IEEE.

关键词： Linear programming

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Enhancing Traffic Flow Forecasting with Spatio-Temporal Information: A Case Study on Highway Networks in Belgium

Enhancing Traffic Flow Forecasting with Spatio-Temporal Info...

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International Conference on instrumentation control and Automation (ICA)

作者： Muhammad Farhan Fathurrahman Arne Catteeuw Sidharta Gautama Angel Lopez Aguirre Endra Joelianto Herman Y. Sutarto Department Of Industrial Systems Engineering and Product Design Ghent University Ghent Belgium Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia FlandersMake@UGent–Corelab ISyE Lommel Belgium Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

As the number of vehicles continues to increase every year, it is crucial to monitor traffic conditions effectively. Traffic forecasting serves as a valuable method in traffic management to support decision making. This study investigates the impact of utilizing spatio-temporal data for traffic flow forecasting, as opposed to forecasting each location individually. We compare spatio-temporal Long Short-Term Memory (LSTM), a machine-learning technique that utilizes spatially correlated sensor data in a network, and compare this to conventional LSTM and Seasonal ARIMA (SARIMA). Experiments have been conducted on counting loop data of a highway network in Belgium. We have investigated the performances of the forecasting model for different prediction horizons. The results show that spatial information improves the performance of the forecasting model and reduces the training time required. Further analysis show that the spatio-temporal LSTM improves majorities of detectors while the minorities detectors are degraded which imply the importances of network selection. The computational load of the spatio-temporal LSTM model is minimally impacted by the number of sensors in the network thus making it scalable. The results show that longer prediction horizons degrade the forecasting performance but the impact up to a 12 hour-horizon is not significant.

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The Regulation of a Quadrotor UAV Carrying a Pendulum using Receding Horizon control

The Regulation of a Quadrotor UAV Carrying a Pendulum using ...

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International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Tua A. Tamba Yul Y. Nazaruddin Endang Juliastuti Center for Control Automation & Systems Engineering Parahyangan Catholic University Bandung Indonesia National Center for Sustainable Transportation Technology Bandung Indonesia Instrumentation & Control Research Group Institut Teknologi Bandung

ISBN: (数字)9781728110974

ISBN: (纸本)9781728110981

关键词： Optimization Regulation Mathematical model Electrical engineering Vehicle dynamics Task analysis Simulation

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Polynomial-Based Linear Programming Relaxation of Sensor Network Localization Problem

Polynomial-Based Linear Programming Relaxation of Sensor Net...

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International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Tua A. Tamba Yul Y. Nazaruddin Center for Control Automation & Systems Engineering Parahyangan Catholic University Bandung Indonesia National Center for Sustainable Transportation Technology Bandung Indonesia Instrumentation & Control Research Group Institut Teknologi Bandung

ISBN: (数字)9781728110974

ISBN: (纸本)9781728110981

关键词： Optimization Wireless sensor networks Noise measurement Wireless communication Linear programming Electrical engineering Programming

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Pole placement enhancement of a constrained greenhouse SISO system 1

Pole placement enhancement of a constrained greenhouse SISO ...

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1st International Conference on Innovative research in Applied Science, Engineering and Technology, IRASET 2020

作者： Hamidane, H. Elfaiz, S. Guerbaoui, M. Ed-Dahhak, A. Lachhab, A. Bouchikhi, B. Moulay Ismaïl University Department of Electrical Engineering Modelling Systems Control and Telecommunications Team High School of Technology Meknes Morocco Ibn Zohr University Research team on Energy and Sustainable Development Guelmim Morocco Moulay Ismaïl University Department of Physics Sensor Electronic and Instrumentation Group Faculty of Sciences Meknes Morocco

ISBN: (纸本)9781728149790

In this paper, we present an application of a pole placement technique related to the stability analysis for a linear constrained system. In this regard some of the main approaches that have been used in the last decades dealing with the pole placement will be engaged. Concepts and methods involved in this work include positive invariance as an efficient notion for the pole placement amelioration of a modern SISO system. The state feedback will enhance the stabily of the closed loop system under the notion of constrained control. For this aim, a greenhouse system, is engaged and a linear discrete time state space model, which fits properly the acquired data of the greenhouse, was identified by the mean of the subspace system identification (N4sid) algorithm. The obtained model will be used in order to develop and calculate the state feedback gain based on the so-called Sylvester algebric equation and one of the pole placement techniques algorithm to ameliorate the closedloop pole placement of the system with constraints on the control. © 2020 IEEE.

关键词： Linear systems

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Robust Stabilization of T-S Fuzzy Stochastic Descriptor systems via Integral Sliding Modes

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2736-2749页

作者： Li, Jinghao Zhang, Qingling Yan, Xing-Gang Spurgeon, Sarah K. Institute of Systems Science State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Instrumentation Control and Embedded Systems Research Group School of Engineering and Digital Arts University of Kent Canterbury U.K. Department of Electronic and Electrical Engineering University College London London U.K.

This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.

关键词： Integral sliding mode control inverted pendulum nonparallel distributed compensation (Non-PDC) robust stabilization Takagi-Sugeno (T-S) fuzzy stochastic descriptor systems

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