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Automating RTGC with PID Control: Utilizing Camera-Based Image Processing and Object Detection

IFAC-PapersOnLine 2024年第7期58卷 299-304页

作者： Steven Bandong Yul Y. Nazaruddin Augie Widyotriatmo Muhammad R. Miransyahputra Yan Setiaji Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

The high traffic in the container yard requires effective management, and one method to address this is through automation. The Rubber Tyred Gantry Crane (RTGC) plays a crucial role in container yards. Automating the RTGC involves determining the container’s location and sway angle to provide feedback for the control system. The advancements in computer vision technology offer a unique solution to tackle these challenges. This paper proposes image processing as a means to sense the sway angle and MobileNet SSD to detect the container’s location. The proposed method yields accurate measurement results and is integrated with optimized PID-PD for position and sway angle control in RTGC. The effectiveness of the proposed method is demonstrated through successful performance in both simulation and experiments conducted on a laboratory-scale RTGC prototype.

关键词： port automation RTGC control system computer vision optimization camera based sensor

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Quantitative EEG Analysis Based on PSD and eLORETA-Source Localization Approach in Spatial Auditory Process

Quantitative EEG Analysis Based on PSD and eLORETA-Source Lo...

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International Conference on Instrumentation Control and Automation (ICA)

作者： Masitoh Masitoh Suprijanto Suprijanto R. S. Joko Sarwono Doctoral Program of Engineering Physics Institut Teknologi Bandung Bandung Indonesia Instrumentation and Control Research Group Institut Teknologi Bandung Bandung Indonesia Engineering Physics Research Group Institut Teknologi Bandung Bandung Indonesia

The advancement of spatial audio technology has been driven by the human capacity for spatial auditory, enabling immersive auditory experiences that replicate real-life sound environments. Understanding how the brain encodes spatial auditory processes has emerged as a growing area of research. Electroencephalography (EEG), a non-invasive modality with high temporal resolution, offers an ideal means to study brain responses to moving sound stimuli. This study aims to compare quantitative EEG methods derived from direct EEG recordings, focusing on EEG temporal features such as Power Spectral Density (PSD), as well as EEG source localization using eLORETA. Two types of audio stimuli, stereo audio and spatial audio, delivered through headsets attached directly to both ears, were investigated. When exposed to the spatial audio stimulus, there was a notable increase in the mean PSD within the Theta, Alpha, and Beta frequency bands in the auditory cortex (channel T3, T4, T5, and T6). The most significant increase was observed in the Beta frequency band of 145.601 µV 2 /Hz in T4, indicating heightened focus experienced by the subjects compared to the stereo audio stimulus. Furthermore, EEG source localization using eLORETA revealed distinct activation in the frontal area during the second experiment involving the spatial audio stimulus. Specifically, there was a significant increase (p>0.05) in current density within the frontal regions of the brain, including Brodmann Area (BA) 6 and 9, which are associated with selective attention and spatial orientation. These findings highlight the practicality of the employed methods and their potential to shed light on brain activity during spatial auditory processes.

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Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing Control of Nutrient Levels, Climate Conditions, and Plant Health

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

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International Conference on Technology, Informatics, Management, engineering, and Environment (TIME-E)

作者： Albert Good Fried Panggabean Rahmat Romadhon Ramot Lubis Endra Joelianto Doctoral Program in Engineering Physics Institut Teknologi Bandung Bandung Indonesia Faculty of Informatics and Electrical Engineering Institut Teknologi Del Toba Indonesia Engineering Physics Study Program Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350364750

ISBN: (纸本)9798350364767

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health.

关键词： Smart agriculture Precision agriculture Reinforcement learning Humidity Aerospace electronics Nutrients Temperature control Informatics Monitoring Farming

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Nano-Flower MnO 2 Coated Graphene Composite Electrodes for Energy Storage Devices

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MRS Online Proceedings Library 2011年第1期1303卷 157-162页

作者： Qian Cheng Jie Tang Jun Ma Han Zhang Norio Shinya Lu-Chang Qin National Institute for Materials Science Sengen Japan Doctoral Program in Materials Science and Engineering University of Tsukuba Tennodai Japan Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel Hill USA

Graphene, two-dimensional layers of sp2-bonded carbon, has many unique properties. In this paper, graphene is decorated with flower-like MnO2 nanostructures for the application in energy storage devices. The as-prepared graphene and MnO2 nano-flowers, which were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), were assembled into an asymmetric supercapacitor. The specific capacitance of the graphene electrode reached 245 F/g at a charging current of 1 mA. The MnO2 nano-flowers which consisted of tiny rods with a diameter of less than 10 nm were coated onto the graphene electrodes by electrodeposition. The specific capacitance after the MnO2 deposition is 328 F/g at the charging current of 1 mA with an energy density of 11.4Wh/kg and power density of 25.8 kW/kg. This work suggests that our graphene-based electrodes can be a promising candidate for high-performance energy storage devices.

关键词： electrodeposition energy storage C

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Constrained and Unconstrained Nonlinear Control of Rubber Tyred Gantry Crane (RTGC) with DC Motor Using Sliding Mode Controller

Constrained and Unconstrained Nonlinear Control of Rubber Ty...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Cristian MP Napitupulu Steven Bandong Yul Yunazwin Nazaruddin Parsaulian I. Siregar Department of Engineering Physics Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Department of Engineering Physics Instrumentation and Control Research Group Institut Teknologi Bandung Bandung Indonesia

The increasing exchange of goods between countries and continents necessitates efficient transportation facilities, with cargo seaports playing a vital role. Within each cargo seaport, the Rubber Tyred Gantry Crane (RTGC) stands out as crucial heavy equipment that requires automation to manage heavy cargo traffic and eliminate bottlenecks. While linear control methods are commonly employed to address this challenge, the inherent nonlinear behavior of the system must be considered. This paper focuses on designing a nonlinear control method, specifically the Sliding Mode Controller (SMC), to create an effective MIMO controller for managing the position, cable length, and sway of the gantry crane system. Two DC motors serve as actuators for controlling the trolley position and cable length, which hoists the container. The nonlinear gantry crane model, integrated with the nonlinear DC motor model, is elaborately derived. Subsequently, the designed non-linear SMC control law and sliding surface are simulated to assess control performance. Acknowledging the limitation of the power source and DC motor specifications, the paper also explores control performance when the voltage to control R TGC is constrained within a specified range. The results demonstrate that the proposed method yields excellent control performance for both constrained and unconstrained control outputs.

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Heterogeneous remote computing system for computational astrophysics with OmniRPC

Heterogeneous remote computing system for computational astr...

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Workshops on Applications and the Internet (SAINT)

作者： K. Onuma T. Boku M. Sato D. Takahashi H. Susa M. Umemura Doctoral Program of Systems and Information Engineering University of Tsukuba Japan Institute of Information Sciences and Electronics Centre for Computational Physics University of Tsukuba Japan Department of Physics Rikkyo University Japan Institute of Physics Centre for Computational Physics University of Tsukuba Japan

We have developed a hybrid computing system named HMCS-G (Grid-enabled Heterogeneous Multi-Computer System) which combines multiple cluster systems and a special purpose machine for gravity calculations. The purpose of HMCS-G is to provide ideal computation environment for computational astrophysics, which requires multiple physics phenomena for precise and detailed simulation. There are two categories of machines required for this system, that is, multiple PC-clusters for general purpose computation such as hydro-dynamics and a special purpose machine GRAPE-6 which calculates gravity for all pairs of particles in the system with very high-speed. These systems are connected with a grid-RPC named OmniRPC which supports Globus and ssh for authentication. Our HMCS-G enables the worldwide access to GRAPE-6 cluster which provides several TFLOPS performance for gravity calculation. All participating PC-clusters share this resource in time sharing manner with grid technology. For efficient usage of GRAPE-6 resource, we modified the original server cluster of it for multiple clients running in various network environment. Currently, precise simulations on galaxy formation are being performed on clusters in several institutes with smoothed particle hydrodynamics and radiative transfer under complete gravity calculation, as the first real application on HMCS-G.

关键词： Astrophysics Gravity Pipelines physics computing Grid computing Computational modeling Authentication Time sharing computer systems File servers Network servers

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DDPG-Based PID Optimal Controller for Position and Sway Angle of RTGC

DDPG-Based PID Optimal Controller for Position and Sway Angl...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Steven Bandong Yul Y. Nazaruddin Endra Joelianto Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Faculty of Industrial Technology Instrumentation and Control Research Group Bandung Indonesia

Increasing global trade requires fast and accurate container transfers by minimizing positional errors and swing angles on the Rubber Tyred Gantry Crane (RTGC) at the container yard causing that the optimization of the controller is a necessity. Currently developing artificial intelligence, namely reinforcement learning based Deep Deterministic Policy Gradient (DDPG) approach, can provide continuous action or output that can be used for controller optimization problems. DDPG can learn from its interactions with the environment, allowing it to identify the best optimal parameter region. This paper proposes DDPG as an PID controller optimizer for position and swing angle of RTGC tested on six episode variations and a trajectory reference. The results garnered from this proposed methodology reveal that the optimal PID parameters perform well across a spectrum of reference trajectories, as well as under varying system parameters such as container masses and rope lengths, as demonstrated by metrics like position and swing angle error, rise time, settling time, and overshoot.

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Optimal RTGC Non-linear Control System Based on Sliding Mode Controller

Optimal RTGC Non-linear Control System Based on Sliding Mode...

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SICE International Symposium on Control Systems (ISCS)

作者： Steven Bandong Cristian MP Napitupulu Yul Yunazwin Nazaruddin Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Engineering Physics Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Department of Engineering Physics Instrumentation and Control Research Group Institut Teknologi Bandung Bandung Indonesia National Center for Sustainable Transportation Technology Institut Teknologi Bandung Bandung Indonesia

The high traffic of containers between countries and continents demands the implementation of automation at cargo seaports. Rubber Tyred Gantry Crane (RTGC) is one of the main components for loading and unloading at container yards which needs to move the container accurately to the desired position and minimize the sway during this process. This paper attempts to examine non-linear control using the sliding mode controller (SMC) method for MIMO control problems in RTGC. The control objective is to reduce the swing angle and move the container to the desired position and height by means of the force of two motors on RTGC. The detailed derivation of the nonlinear RTGC model, the design of SMC and its sliding surface are introduced in this paper. In order to optimize the performance of the SMC control action, the Particle Swarm Optimization (PSO) and Grid search methods are employed in the investigation. The obtained results demonstrate that the SMC exhibits satisfactory control performance and effectively reduces chattering across various initial conditions and system parameters.

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Deep Learning Methods for Plankton Identification: A Bibliometric Analysis and General Review 1

Deep Learning Methods for Plankton Identification: A Bibliom...

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1st International Conference on Smart Technology, Applied Informatics, and engineering, APICS 2022

作者： Ardhi, Ovide Decroly Wisnu Soeprobowati, Tri Retnaningsih Adi, Kusworo Prakasa, Esa Rachman, Arief School of Postgraduate Studies Universitas Diponegoro Doctoral of Information System Program Semarang Indonesia Vocational School Universitas Sebelas Maret Department of Informatics Engineering Surakarta Indonesia Universitas Diponegoro Faculty of Science of Mathematics Department of Biology Semarang Indonesia Universitas Diponegoro Faculty of Science of Mathematics Department of Physics Semarang Indonesia Bandung Indonesia Jakarta Indonesia

ISBN: (数字)9781665489850

ISBN: (纸本)9781665489850

This study investigates trends in deep learning research on microscopic images to identify and classify plankton. We performed a bibliometric analysis using VOSviewer to display the visualizations. The first step is to extract the relevant journals from the Scopus database. Extraction from relevant journals found 42 articles, including 21 journals and 21 conferences. We analyzed publication trends and analyzes of co-authorship, co-occurrence, and citations. In addition, it examines the collaborative relationship between authors by country, the emergence of co-author keywords, and the citation of journal sources. We found that the researchers performed plankton classification tasks that achieved high accuracy (>90%). The plankton identification method uses a deep learning architecture based on the Convolutional Neural Network. Among the architectures are AlexNet, GoogleNet, InceptionV3, VGGNet (16.19), ResNet (50.101), DenseNet, NasNet, MobileNetV2, ResidualNet, Shufflenet, EfficienNet, and CapsNet. Some researchers combine CNN with SparseConvNets, LMP, SVM, MorphoCluster, and Quantification Algorithm (CC, AC, PCC, PAC, Hdy). Some methods also implement transfer learning, fine-tuning, and advanced features. In addition to the CNN approach, End-to-End Object Detection with transformers is one of the new approaches in the future to identify plankton. © 2022 IEEE.

关键词： Deep learning

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Nano-flower MnO2 coated graphene composite electrodes for energy storage devices

Nano-flower MnO2 coated graphene composite electrodes for en...

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2010 MRS Fall Meeting

作者： Cheng, Qian Tang, Jie Ma, Jun Zhang, Han Shinya, Norio Qin, Lu-Chang National Institute for Materials Science 1-2-1 Sengen Tsukuba 305-0047 Japan Doctoral Program in Materials Science and Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba 305-8577 Japan Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel Hill NC 27599-3255 United States

ISBN: (纸本)9781605112800

Graphene, two-dimensional layers of sp2-bonded carbon, has many unique properties. In this paper, graphene is decorated with flower-like MnO2 nanostructures for the application in energy storage devices. The as-prepared graphene and MnO2 nano-flowers, which were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), were assembled into an asymmetric supercapacitor. The specific capacitance of the graphene electrode reached 245 F/g at a charging current of 1 mA. The MnO2 nano-flowers which consisted of tiny rods with a diameter of less than 10 nm were coated onto the graphene electrodes by electrodeposition. The specific capacitance after the MnO2 deposition is 328 F/g at the charging current of 1 mA with an energy density of 11.4 Wh/kg and power density of 25.8 kW/kg. This work suggests that our graphene-based electrodes can be a promising candidate for high-performance energy storage devices. © 2011 Materials Research Society.

关键词： Graphene

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