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Electronics
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Real-Time Control of Embedded Systems
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Real-Time Control of Embedded Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 34845

Special Issue Editors

Prof. Dr. Deok-Hwan Kim

E-Mail Website
Guest Editor
Department of Electronic Engineering, Inha University, Incheon 22212, Republic of Korea
Interests: embedded and real-time systems; cyber-physical systems (CPS) and artificial intelligence (AI); edge computing and Internet of Things (IoT); embedded software for robots and vehicles
Special Issues, Collections and Topics in MDPI journals
Dr. Mehdi Pirahandeh

E-Mail Website
Guest Editor
Department of Electronic Engineering, Inha University, Incheon 22212, Korea
Interests: high-performance cloud storage system; edge computing; parallel computing; embedded software for advanced manufacturing; Internet of Things (IoT); big data and artificial intelligence

Special Issue Information

Dear Colleagues,

The real-time control of embedded systems has become a necessity in almost every aspect of life. A higher level of control of embedded systems gives users a wide range of flexibility. Many such systems are mission-critical and latency-sensitive embedded systems. Embedded systems’ controllers are implemented locally to complete various sets of related tasks. Embedded controllers have a wide variety of uses that vary from microcontrollers to consumer electronics, weapons to medical devices, and edge-level controllers to cloud-level control systems. Real-time control of embedded systems powered by artificial intelligence (AI) will revolutionize how we control environments including factories, workplaces, transportation systems, and power/water/gas grids. For example, AI-powered robots are rapidly becoming capable of controlling multiple tasks and learning from experience while interacting with humans.

This Special Issue welcomes contributions on novel ideas related to embedded systems in various domains, such as Industrial Automation, Manufacturing, Robotics, Automotive, Appliance Automation, Healthcare, Wearable Systems, Energy Systems, Smart Grid and Smart Cities, including, but not limited to, the following topics:

  • AI-powered real-time control for embedded systems;
  • Modelling and simulation of real-time control for embedded systems;
  • Sensing and perception of real-time controllers for embedded systems;
  • Enhancing the energy efficiency of real-time control for embedded systems;
  • Reliable and fault-tolerant real-time controllers for IoT devices;
  • Lessons learned from the large-scale real-time control of embedded systems.

Prof. Dr. Deok-Hwan Kim
Dr. Mehdi Pirahandeh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Embedded systems
  • Parallel computing
  • Deep learning
  • Artificial intelligence
  • Internet of Things
  • Distributed systems
  • Real-time operating systems
  • Cyber-physical systems
  • Real-time embedded systems
  • Digital signal processing
  • Edge computing
  • Fault-tolerant applications

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Published Papers (15 papers)

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Research

17 pages, 1823 KiB  
Article
Design and Implementation of an MIPI A-PHY Retransmission Layer for Automotive Applications
by Sang-ung Shin, Jin-Ku Kang and Yongwoo Kim
Electronics 2023, 12(20), 4243; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics12204243 - 13 Oct 2023
Viewed by 1332
Abstract
Recently, with the development of automobile technologies such as advanced driver assistance systems (ADASs), the performance and number of cameras and displays required for a vehicle have significantly increased. Therefore, the need for in-vehicle high-speed data transmission has increased, but there is difficulty [...] Read more.
Recently, with the development of automobile technologies such as advanced driver assistance systems (ADASs), the performance and number of cameras and displays required for a vehicle have significantly increased. Therefore, the need for in-vehicle high-speed data transmission has increased, but there is difficulty in handling the required high-speed data transmission in existing in-vehicle networks. The MIPI A-PHY interface for automobiles has been proposed as a new standard to solve this issue. To ensure data transmission in noisy automotive environments, the A-PHY interface contains an added retransmission (RTS) layer within the new physical layer. In this paper, we propose and design in detail the structure of an RTS layer presented in the standard A-PHY interface. The proposed RTS layer was designed to satisfy the RTS specification of the MIPI A-PHY standard and was verified through simulations. Moreover, the A-PHY SerDes environment was configured in an FPGA using a Xilinx KC705 FPGA development board and an FPGA Mezzanine Card (FMC) loopback module, and RTS layer operation was verified through the process of transmitting video data to the A-Packet. The A-PHY interface with the RTS layer designed on the FPGA uses 3924 LUTs, 2019 registers, and 132 block memories and operates at a maximum speed of 200 MHz. In addition, as a result of designing the A-PHY interface as an ASIC implementation using the Synopsys SAED 28 nm process, the number of logic gates is 25 K, the chip area is 0.40 mm2, and the maximum operating speed is 200 MHz. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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29 pages, 15150 KiB  
Article
Real-Time Embedded System-Based Approach for Sensing Power Consumption on Motion Profiles
by Luis F. Olmedo-García, José R. García-Martínez, Edson E. Cruz-Miguel, Omar A. Barra-Vázquez, Mario Gónzalez-Lee and Trinidad Martínez-Sánchez
Electronics 2023, 12(18), 3853; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics12183853 - 12 Sep 2023
Viewed by 825
Abstract
This paper discusses the energy consumption of three parabolic, trapezoidal, and S-curve profiles when implemented using an embedded system. In addition, it presents an alternative methodology for implementing motion controllers using an Advanced RISC Machine (ARM) microcontroller, which computes the trajectory and performs [...] Read more.
This paper discusses the energy consumption of three parabolic, trapezoidal, and S-curve profiles when implemented using an embedded system. In addition, it presents an alternative methodology for implementing motion controllers using an Advanced RISC Machine (ARM) microcontroller, which computes the trajectory and performs the control action in hard real-time. We experimented using a linear plant composed of a direct current (DC) motor coupled to an endless screw where a carriage was mounted. It can move mechanically along a rail at a distance of 1.16 m. A 4096 pulses per revolution (PPR) encoder was connected to the motor to calculate position and angular velocity. A Hall-effect-based current sensor was used to assess energy consumption. We conducted 40 tests for each profile to compare the energy consumption for the three motion profiles, considering cases with and without load on the carriage. We determined that the parabolic profile provides 22.19% lower energy consumption than the other profiles considered in this study, whereas the S-curve profile exhibited the highest energy consumption. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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16 pages, 1453 KiB  
Article
A Multi-Modal Story Generation Framework with AI-Driven Storyline Guidance
by Juntae Kim, Yoonseok Heo, Hogeon Yu and Jongho Nang
Electronics 2023, 12(6), 1289; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics12061289 - 08 Mar 2023
Viewed by 3150
Abstract
An automatic story generation system continuously generates stories with a natural plot. The major challenge of automatic story generation is to maintain coherence between consecutive generated stories without the need for human intervention. To address this, we propose a novel multi-modal story generation [...] Read more.
An automatic story generation system continuously generates stories with a natural plot. The major challenge of automatic story generation is to maintain coherence between consecutive generated stories without the need for human intervention. To address this, we propose a novel multi-modal story generation framework that includes automated storyline decision-making capabilities. Our framework consists of three independent models: a transformer encoder-based storyline guidance model, which predicts a storyline using a multiple-choice question-answering problem; a transformer decoder-based story generation model that creates a story that describes the storyline determined by the guidance model; and a diffusion-based story visualization model that generates a representative image visually describing a scene to help readers better understand the story flow. Our proposed framework was extensively evaluated through both automatic and human evaluations, which demonstrate that our model outperforms the previous approach, suggesting the effectiveness of our storyline guidance model in making proper plans. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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18 pages, 1945 KiB  
Article
Deletion-Based Tangle Architecture for Edge Computing
by Khikmatullo Tulkinbekov and Deok-Hwan Kim
Electronics 2022, 11(21), 3488; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11213488 - 27 Oct 2022
Viewed by 1328
Abstract
IOTA Tangle offers a promising approach for distributed ledger technology with the capability to compete with the traditional blockchain. To enable microtransactions the Internet of things (IoT) environment, IOTA employs a direct acrylic graph that ensures the integrity and immutability of the transactions. [...] Read more.
IOTA Tangle offers a promising approach for distributed ledger technology with the capability to compete with the traditional blockchain. To enable microtransactions the Internet of things (IoT) environment, IOTA employs a direct acrylic graph that ensures the integrity and immutability of the transactions. However, IoT data exhibit time sensitivity, wherein the value is lost after a period. Storing these temporary data for immutable storage would not be affordable in the distributed ledger. This study proposes a novel approach—referred to as D-Tangle—that enables data deletions in the Tangle architecture. To achieve this goal, D-Tangle divides transactions into three categories based on their expiration features and employs the climb-up writing technique. Extensive evaluations prove that D-Tangle enables instant deletions in finite lifetime data. Moreover, immutability and deletion upon request are guaranteed for unknown lifetime data. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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14 pages, 2470 KiB  
Article
Task-Space Cooperative Tracking Control for Networked Uncalibrated Multiple Euler–Lagrange Systems
by Zhuoqun Zhao, Jiang Wang and Hui Zhao
Electronics 2022, 11(15), 2449; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11152449 - 06 Aug 2022
Cited by 1 | Viewed by 1027
Abstract
Task-space cooperative tracking control of the networked multiple Euler–Lagrange systems is studied in this paper. On the basis of establishing kinematic and dynamic modeling of a Euler–Lagrange system, an innovative task-space coordination controller is designed to deal with the time-varying communicating delays and [...] Read more.
Task-space cooperative tracking control of the networked multiple Euler–Lagrange systems is studied in this paper. On the basis of establishing kinematic and dynamic modeling of a Euler–Lagrange system, an innovative task-space coordination controller is designed to deal with the time-varying communicating delays and uncertainties. First, in order to weaken the influence of the uncertainty of kinematic and dynamic parameters on the control error of the system, the product of the Jacobian matrix and the generalized spatial velocity are linearly parameterized; thus, the unknown parameters are separated from known parameters. The online estimation of uncertain parameters is realized by designing parameters and by proposing new adaptive laws for the dynamic and kinematic parameters. Furthermore, to describe the transmission of time-varying delay errors among networked agents, a new error term is introduced, obtained by adding the observation error and tracking error, and the coefficient of the network mutual coupling term related to the time-varying delay rate is added with reference to the generalized space velocity and task-space velocity of the Lagrange systems. In the end, the influence of the time-varying delay on the cooperative tracking control error of the networked multiple Euler–Lagrange systems is eliminated. With the help of Lyapunov stability theory, the tracking errors and synchronization errors of this system are calculated by introducing the Lyapunov–Krasovskii functional; the asymptotic convergence results rigorously prove the stability of the adaptive cooperative control systems. The simulation results verify the excellent performance of the controller. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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10 pages, 2255 KiB  
Article
Audio-Based Wildfire Detection on Embedded Systems
by Hung-Tien Huang, Austin R. J. Downey and Jason D. Bakos
Electronics 2022, 11(9), 1417; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11091417 - 28 Apr 2022
Cited by 2 | Viewed by 1954
Abstract
The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and [...] Read more.
The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and preventing loss of life. This work presents a machine learning wildfire detecting data pipeline that can be deployed on embedded systems in remote locations. The proposed data pipeline consists of three main steps: audio preprocessing, feature engineering, and classification. Experiments show that the proposed data pipeline is capable of detecting wildfire effectively with high precision and is capable of detecting wildfire sound over the forest’s background soundscape. When being deployed on a Raspberry Pi 4, the proposed data pipeline takes 66 milliseconds to process a 1 s sound clip. To the knowledge of the author, this is the first edge-computing implementation of an audio-based wildfire detection system. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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19 pages, 3046 KiB  
Article
Advanced Intrusion Detection Combining Signature-Based and Behavior-Based Detection Methods
by Hee-Yong Kwon, Taesic Kim and Mun-Kyu Lee
Electronics 2022, 11(6), 867; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11060867 - 09 Mar 2022
Cited by 16 | Viewed by 4021
Abstract
Recently, devices in real-time systems, such as residential facilities, vehicles, factories, and social infrastructure, have been increasingly connected to communication networks. Although these devices provide administrative convenience and enable the development of more sophisticated control systems, critical cybersecurity concerns and challenges remain. In [...] Read more.
Recently, devices in real-time systems, such as residential facilities, vehicles, factories, and social infrastructure, have been increasingly connected to communication networks. Although these devices provide administrative convenience and enable the development of more sophisticated control systems, critical cybersecurity concerns and challenges remain. In this paper, we propose a hybrid anomaly detection method that combines statistical filtering and a composite autoencoder to effectively detect anomalous behaviors possibly caused by malicious activity in order to mitigate the risk of cyberattacks. We used the SWaT dataset, which was collected from a real water treatment system, to conduct a case study of cyberattacks on industrial control systems to validate the performance of the proposed approach. We then evaluated the performance of the proposed hybrid detection method on a dataset with two time window settings for the composite autoencoder. According to the experimental results, the proposed method improved the precision, recall, and F1-score by up to 0.008, 0.067, and 0.039, respectively, compared to an autoencoder-only approach. Moreover, we evaluated the computational cost of the proposed method in terms of execution time. The execution time of the proposed method was reduced by up to 8.03% compared to that of an autoencoder-only approach. Through the experimental results, we show that the proposed method detected more anomalies than an autoencoder-only detection approach and it also operated significantly faster. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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21 pages, 3003 KiB  
Article
BloSM: Blockchain-Based Service Migration for Connected Cars in Embedded Edge Environment
by Srinidhi Kanagachalam, Khikmatullo Tulkinbekov and Deok-Hwan Kim
Electronics 2022, 11(3), 341; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11030341 - 23 Jan 2022
Cited by 4 | Viewed by 2473
Abstract
Edge computing represents the future of computing paradigms that perform tasks near the user plane. The integration of blockchain with edge computing provides the added advantage of secured and trusted communication. In this paper, we propose a blockchain-based service migration by developing edge [...] Read more.
Edge computing represents the future of computing paradigms that perform tasks near the user plane. The integration of blockchain with edge computing provides the added advantage of secured and trusted communication. In this paper, we propose a blockchain-based service migration by developing edge clusters using NVIDIA Jetson boards in an embedded edge environment, using containers and Kubernetes as a container orchestration capable of handling real-time computation-intensive deep learning tasks. Resource constraints in the edge and client movement are the proposed scenarios for service migration. Container migration due to mobile clients is integrated with blockchain to find a suitable destination, meta-based node evaluation, and secured data transfer in the connected car environment. Each service request migration takes, on average, 361 ms. The employed container migration method takes 75.11 s and 70.46 s to migrate application containers that use NVIDIA CUDA Toolkit. Finally, we evaluate the efficiency of blockchain to find the destination node through performance parameters such as latency, throughput, storage, and bandwidth. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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17 pages, 1742 KiB  
Article
AMROFloor: An Efficient Aging Mitigation and Resource Optimization Floorplanner for Virtual Coarse-Grained Runtime Reconfigurable FPGAs
by Zeyu Li, Zhao Huang, Quan Wang and Junjie Wang
Electronics 2022, 11(2), 273; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11020273 - 15 Jan 2022
Cited by 1 | Viewed by 1333
Abstract
With the rapid reduction of CMOS process size, the FPGAs with high-silicon accumulation technology are becoming more sensitive to aging effects. This reduces the reliability and service life of the device. The offline aging-aware layout planning based on balance stress is an effective [...] Read more.
With the rapid reduction of CMOS process size, the FPGAs with high-silicon accumulation technology are becoming more sensitive to aging effects. This reduces the reliability and service life of the device. The offline aging-aware layout planning based on balance stress is an effective solution. However, the existing methods need to take a long time to solve the floorplanner, and the corresponding layout solutions occupy many on-chip resources. To this end, we proposed an efficient Aging Mitigation and Resource Optimization Floorplanner (AMROFloor) for FPGAs. First, the layout solution is implemented on the Virtual Coarse-Grained Runtime Reconfigurable Architecture, which contributes to avoiding rule constraints for placement and routing. Second, the Maximize Reconfigurable Regions Algorithm (MRRA) is proposed to quickly determine the RRs’ number and size to save the solving time and ensure an effective solution. Furthermore, the Resource Combination Algorithm (RCA) is proposed to optimize the on-chip resources, reducing the on-Chip Resource Utilization (CRU) while achieving the same aging relief effect. Experiments were simulated and implemented on Xilinx FPGA. The results demonstrate that the AMROFloor method designed in this paper can extend the Mean Time to Failure (MTTF) by 13.8% and optimize the resource overhead by 19.2% on average compared to the existing aging-aware layout solutions. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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15 pages, 2517 KiB  
Article
Human–Machine Interaction in Driving Assistant Systems for Semi-Autonomous Driving Vehicles
by Heung-Gu Lee, Dong-Hyun Kang and Deok-Hwan Kim
Electronics 2021, 10(19), 2405; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10192405 - 01 Oct 2021
Cited by 3 | Viewed by 3637
Abstract
Currently, the existing vehicle-centric semi-autonomous driving modules do not consider the driver’s situation and emotions. In an autonomous driving environment, when changing to manual driving, human–machine interface and advanced driver assistance systems (ADAS) are essential to assist vehicle driving. This study proposes a [...] Read more.
Currently, the existing vehicle-centric semi-autonomous driving modules do not consider the driver’s situation and emotions. In an autonomous driving environment, when changing to manual driving, human–machine interface and advanced driver assistance systems (ADAS) are essential to assist vehicle driving. This study proposes a human–machine interface that considers the driver’s situation and emotions to enhance the ADAS. A 1D convolutional neural network model based on multimodal bio-signals is used and applied to control semi-autonomous vehicles. The possibility of semi-autonomous driving is confirmed by classifying four driving scenarios and controlling the speed of the vehicle. In the experiment, by using a driving simulator and hardware-in-the-loop simulation equipment, we confirm that the response speed of the driving assistance system is 351.75 ms and the system recognizes four scenarios and eight emotions through bio-signal data. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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11 pages, 21022 KiB  
Article
A Flexible Input Mapping System for Next-Generation Virtual Reality Controllers
by Eun-Seok Lee and Byeong-Seok Shin
Electronics 2021, 10(17), 2149; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10172149 - 03 Sep 2021
Cited by 4 | Viewed by 2239
Abstract
This paper proposes an input mapping system that can transform various input signals from next-generation virtual reality devices to suit existing virtual reality content. Existing interactions of virtual reality content are developed based on input values for standardized commercial haptic controllers. This prevents [...] Read more.
This paper proposes an input mapping system that can transform various input signals from next-generation virtual reality devices to suit existing virtual reality content. Existing interactions of virtual reality content are developed based on input values for standardized commercial haptic controllers. This prevents the challenge of new ideas in content. However, controllers that are not compatible with existing virtual reality content have to take significant risks until commercialization. The proposed system allows content developers to map streams of new input devices to standard input events for use in existing content. This allows the reuse of code from existing content, even with new devices, effectively reducing development tasks. Further, it is possible to define a new input method from the perspective of content instead of the sensing results of the input device, allowing for content-specific standardization in content-oriented industries such as games and virtual reality. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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14 pages, 4677 KiB  
Article
Low-Memory Indoor Positioning System for Standalone Embedded Hardware
by Han Jun Bae and Lynn Choi
Electronics 2021, 10(9), 1059; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10091059 - 29 Apr 2021
Cited by 1 | Viewed by 1615
Abstract
As the proportion and importance of the indoor spaces in daily life are gradually increasing, spatial information and personal location information become more important in indoor spaces. In order to apply indoor positioning technologies in any places and for any targets inexpensively and [...] Read more.
As the proportion and importance of the indoor spaces in daily life are gradually increasing, spatial information and personal location information become more important in indoor spaces. In order to apply indoor positioning technologies in any places and for any targets inexpensively and easily, the system should utilize simple sensors and devices. In addition, due to the scalability, it is necessary to perform indoor positioning algorithms on the device itself, not on the server. In this paper, we construct standalone embedded hardware for performing the indoor positioning algorithm. We use the geomagnetic field for indoor localization, which does not require the installation of infrastructure and has more stable signal strength than RF RSS. In addition, we propose low-memory schemes based on the characteristics of the geomagnetic sensor measurement and convergence of the target’s estimated positions in order to implement indoor positioning algorithm to the hardware. We evaluate the performance in two testbeds: Hana Square (about 94 m × 26 m) and SK Future Hall (about 60 m × 38 m) indoor testbeds. We can reduce flash memory usage to 16.3% and 6.58% for each testbed and SRAM usage to 8.78% and 23.53% for each testbed with comparable localization accuracy to the system based on smart devices without low-memory schemes. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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12 pages, 1189 KiB  
Article
A Distributed Edge-Based Scheduling Technique with Low-Latency and High-Bandwidth for Existing Driver Profiling Algorithms
by Mehdi Pirahandeh, Shan Ullah and Deok-Hwan Kim
Electronics 2021, 10(8), 972; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10080972 - 19 Apr 2021
Cited by 1 | Viewed by 1683
Abstract
The gradual increase in latency-sensitive, real-time applications for embedded systems encourages users to share sensor data simultaneously. Streamed sensor data have deficient performance. In this paper, we propose a new edge-based scheduling method with high-bandwidth for decreasing driver-profiling latency. The proposed multi-level memory [...] Read more.
The gradual increase in latency-sensitive, real-time applications for embedded systems encourages users to share sensor data simultaneously. Streamed sensor data have deficient performance. In this paper, we propose a new edge-based scheduling method with high-bandwidth for decreasing driver-profiling latency. The proposed multi-level memory scheduling method places data in a key-value storage, flushes sensor data when the edge memory is full, and reduces the number of I/O operations, network latency, and the number of REST API calls in the edge cloud. As a result, the proposed method provides significant read/write performance enhancement for real-time embedded systems. In fact, the proposed application improves the number of requests per second by 3.5, 5, and 4 times, respectively, compared with existing light-weight FCN-LSTM, FCN-LSTM, and DeepConvRNN Attention solutions. The proposed application also improves the bandwidth by 5.89, 5.58, and 4.16 times respectively, compared with existing light-weight FCN-LSTM, FCN-LSTM, and DeepConvRNN Attention solutions. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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15 pages, 10927 KiB  
Article
Performance Analysis of Deep Neural Network Controller for Autonomous Driving Learning from a Nonlinear Model Predictive Control Method
by Taekgyu Lee and Yeonsik Kang
Electronics 2021, 10(7), 767; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10070767 - 24 Mar 2021
Cited by 7 | Viewed by 2544
Abstract
Nonlinear model predictive control (NMPC) is based on a numerical optimization method considering the target system dynamics as constraints. This optimization process requires large amount of computation power and the computation time is often unpredictable which may cause the control update rate to [...] Read more.
Nonlinear model predictive control (NMPC) is based on a numerical optimization method considering the target system dynamics as constraints. This optimization process requires large amount of computation power and the computation time is often unpredictable which may cause the control update rate to overrun. Therefore, the performance must be carefully balanced against the computational time. To solve the computation problem, we propose a data-based control technique based on a deep neural network (DNN). The DNN is trained with closed-loop driving data of an NMPC. The proposed "DNN control technique based on NMPC driving data" achieves control characteristics comparable to those of a well-tuned NMPC within a reasonable computation period, which is verified with an experimental scaled-car platform and realistic numerical simulations. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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13 pages, 667 KiB  
Article
Intelligent Data Fusion and Multi-Agent Coordination for Target Allocation
by Sanguk Noh
Electronics 2020, 9(10), 1563; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9101563 - 24 Sep 2020
Cited by 3 | Viewed by 2179
Abstract
This paper addresses the fusion processing techniques for multi-sensor data perceived through the infrared sensors of military surveillance robots, and proposes their decision-theoretic coordination to effectively monitor multiple targets. To combine the multi-sensor data from the distributed battlefield robots, a set of fusion [...] Read more.
This paper addresses the fusion processing techniques for multi-sensor data perceived through the infrared sensors of military surveillance robots, and proposes their decision-theoretic coordination to effectively monitor multiple targets. To combine the multi-sensor data from the distributed battlefield robots, a set of fusion rules are used to formulate a combined prediction from the multi-source data. The possible type of a target is estimated through the fusion rules. For the identification of targets, agents need to keep track of targets for continuous situation awareness. The coordination of the agents with limited range of surveillance is indispensable for their successful monitoring of multiple targets. For dynamic and flexible coordination, our agents follow the decision-theoretic approach. We implement a military simulator to compare the capabilities of fusion processing and those of coordination, and conduct experiments with our framework in distributed and uncertain battlefield environments. The experimental results show that the fusion process of multi-sensor data from military robots can improve the performance of estimation of the type of a target, and our coordinated agents outperform agents using random strategy for their target selection in various military scenarios. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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