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2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Altınpınar, Ozan Vahit Contarlı, Emre Can Sezer, Volkan Department of Mechatronics Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9798350379433

Mobile robots, which are produced to fulfill certain tasks to make our lives easier, are becoming more and more common in our environment day by day. In the long run, these robots can be more cost-effective, faster, and more efficient than humans in accomplishing tasks. In order for mobile robots to fulfill the tasks, they need to be able to safely navigate to specific destinations without hitting obstacles. Safely reaching a given goal most accurately and shortly is the problem of autonomy. This autonomy problem is divided into sub-problems and algorithms are needed to solve each sub-problem. The main sub-problems in the field of autonomy are localization, mapping, local planning, and global planning. The main purpose of this paper is to describe how the position information computed by a MEKF (Modified Extended Kalman Filter) localization algorithm using the VDPL (Virtual Dynamic Point Landmark) algorithm, which was previously designed in MATLAB, is published to the ROS environment via a topic. This position information can be used together with the local and global planning algorithms in the navigation stack to realize fully autonomous driving capability in a real-time environment. Using these algorithms, full-autonomous driving tests were conducted on the Turtlebot3 mobile robot in a real-time environment according to a predefined scenario. The performance results of both simulation and real-world tests show that the MEKF using the VDPL algorithm outperforms the AMCL algorithm in the navigation stack in both cases. © 2024 IEEE.

关键词： Extended Kalman filters

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Optimal Multi-agent Collision-Free Path Planning with Temporal Logic Constraints 5th

Optimal Multi-agent Collision-Free Path Planning with Tempo...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Zheng, Yiwei Liu, Zhaocong Lai, Aiwen Yu, Xiao Lan, Weiyao Department of Automation Xiamen University Fujian Xiamen361005 China The Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100094 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9789811939976

In this paper, we present a novel optimal multi-agent collision-free path planning algorithm (OMPATL) for the problem of multi-robot path planning with temporal logic constraints. Given a high-level mission specification in the form of linear temporal logic (LTL), OMPATL can automatically synthesize a set of trajectories for the multi-agent system (MAS), which achieves the collision avoidance among agents and minimizes the cost of the maximum traveling time between successive satisfactions. To synthesize the optimal trajectories, the motion of all agents, together with the mission area, is modeled as a weighted team transition system (TS) with a set of atomic propositions (APs). If the collision avoidance were not required, the optimal trajectories would be easily synthesized by an algorithm such as shortest paths. However, once the multi-agent systems are required to be safety-critical and collision-free, these trajectories may become infeasible. In OMPATL, a strategy is proposed for adding a set of transitions including "wait" and "go-back" to each individual TS based on the optimal run which does not consider collision avoidance. Then, the states and transitions with collisions can be removed such that the optimal collision-free trajectories are founded by the synthesis algorithm. The synthesized run balances collision avoidance, mission fulfillment, and optimality. The optimal run is synthesized offline and online adjustments are not needed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Robust control Performance in Uncertain Environments: A Semi-Heuristic Gradient Descent Approach 8

Robust Control Performance in Uncertain Environments: A Semi...

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8th International Conference on Instrumentation, control, and automation, ICA 2023

作者： Ahmed Hassan, Mohammed Elbadri Irham Jambak, Ahmad Bayezit, Ismail Soylemez, Mehmet Turan Istanbul Technical University Department of Control and Automation Engineering Istanbul Turkey Istanbul Technical University Department of Mechatronics Engineering Istanbul Turkey Istanbul Technical University Department of Aeronautical Engineering Istanbul Turkey

ISBN: (纸本)9798350301274

Designing a robust controller for systems with parameter uncertainties is a complex and demanding task. Traditional deterministic and probabilistic approaches may fall short in providing efficient and satisfactory solutions. To address this challenge, we propose a semi-heuristic approach that exploits the Kharitonov theorem to establish an initial point for the gradient descent algorithm. Through an iterative optimization process that incorporates user-defined performance criteria, our approach provide a robust controller with respect to presence of system uncertainties. Numerical simulations validate the effectiveness of our proposed method and highlight its superiority in addressing robust control problems compared with auto-tuned ΡΠ) controller. © 2023 IEEE.

关键词： Optimization

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Parallel Programming in the Hybrid Model on the HPC Clusters 3rd

Parallel Programming in the Hybrid Model on the HPC Clusters

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3rd International Conference on computer Vision, High Performance Computing, Smart Devices, and Networks, CHSN 2022

作者： Rak, Tomasz Department of Computer and Control Engineering Rzeszow University of Technology Powstancow Warszawy 12 Rzeszow35-959 Poland

ISBN: (纸本)9789819966899

Support for an ever-expanding range of distributed and parallel strategies and support for performance analysis are constantly evolving. We propose message passing interface (MPI) and open multi-processing (OpenMP) standards that provide various software development tools covering a wide range of techniques not strictly limited to shared memory. The theoretical part focuses on a general overview of the current capabilities of MPI and OpenMP as application programming interfaces. The authors researched the high-performance computing (HPC) cluster environment, and this work provides results and representative examples. Also, in this study, it has been proven that to obtain favorable processing efficiency and write the code correctly— regardless of the programming paradigm used—it is necessary to know the basic concepts related to a given distributed and parallel architecture. Additionally, in this study, we investigated the need to adapt the tools used to solve a specific problem regarding improving processing efficiency. Finally, we presented that failure to apply a critical section may result in unpredictable results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Message passing

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Augmented hunger games search algorithm using logarithmic spiral opposition-based learning for function optimization and controller design

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Journal of King Saud University - engineering Sciences 2024年第5期36卷 330-338页

作者： Izci, Davut Ekinci, Serdar Eker, Erdal Kayri, Murat Department of Electronics & Automation Batman University Batman72060 Turkey Department of Computer Engineering Batman University Batman72100 Turkey Vocational School of Social Sciences Mus Alparslan University Mus Turkey Department of Computer and Instructional Technology Education Van Yuzuncu Yil University Van Turkey

This paper explains the construction of a novel augmented hunger games search algorithm using a logarithmic spiral opposition-based learning technique. The proposed algorithm (LsOBL-HGS) is used as an efficient tool for both function optimization and controller design. To assess the performance of the algorithm for function optimization, benchmark functions from the CEC2017 test suite were employed and comparisons were made with available and good performing algorithms. In terms of controller design, the proposed LsOBL-HGS algorithm was utilized to design a FOPID controlled magnetic ball suspension system. Comparative assessments were also performed for FOPID controller design, as well using other state-of-the-art methods reported for the magnetic ball suspension system. The results showed that the proposed LsOBL-HGS algorithm has good capability for FOPID controller design employed in a magnetic ball suspension system as it provided an improvement of more than 13% in terms of the transient response-related parameters and more than 34% in terms of bandwidth compared to the best-reported approach used for comparisons. © 2022 Karabuk University

关键词： controllers

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A 6-bit Low-Area Hybrid ADC Design For System-on-Chip Measurements

A 6-bit Low-Area Hybrid ADC Design For System-on-Chip Measur...

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2024 IEEE International Conference on Design, Test and Technology of Integrated Systems, DTTIS 2024

作者： Kolahimahmoudi, Nima Insinga, Giorgio Roggi, Stefano Niederl, Josef Bernardi, Paolo Politecnico di Torino Department of Computer and Control Engineering Turin Italy Infineon Technologies AG Villach Austria

ISBN: (纸本)9798350363128

In recent years, with the declining dimensions of transistors, the system-on-chips (SoCs) have had more physical defects. These physical defects ultimately result in failures that cannot be tolerated in functional safety applications such as electric cars, aerospace, etc. For the digital peripherals of the SoCs, there are well-known methods such as scan chains, whereas there are methods for analog circuits such as analog scan chains or Analog Test Bus (ATB). This paper presents a 6-bit, low-area Analog-to-Digital Converter (ADC) for SoC analog voltage measurements. The advantage of the proposed ADC design is the low additional area cost to the design of the SoC and increasing the testability of the analog peripherals. This ADC design converts the analog signals, which are difficult to observe, to the digital domain, which is easy to route and observe. This architecture comprises two small ADCs for doing coarse and fine conversions. The ADC for the coarse conversion is a 3-bit SAR ADC, and the ADC for the fine conversion is a 3-bit flash ADC. The suggested ADC is implemented using the 130 nm technology of the Infineon, and it has a total area of 0.007 mm2. The fine ADC of the proposed ADC can be shared between the peripherals nearby inside the SoC, and the additional area per peripheral would be only 0.0015 mm2. The Signal-to-Noise Distortion Ratio (SNDR) of the design is 37dB, and the Figure of Merit (FoM) is 2.15 pJ/conv. © 2024 IEEE.

关键词： System-on-chip

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Monte Carlo tree search with state merging for reinforcement learning in Regular Decision Processes

Monte Carlo tree search with state merging for reinforcement...

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2023 International Conference of the Italian Association for Artificial Intelligence Doctoral Consortium, AIxIA-DC 2023

作者： Licks, Gabriel Paludo Sapienza University of Rome Department of Computer Control and Management Engineering Via Ariosto 25 Rome00185 Italy

This research focuses on a novel algorithm for Reinforcement Learning (RL) in Regular Decision Processes (RDPs), a model of non-Markovian decision processes where dynamics and rewards depend on regular properties of the history. Our algorithm is inspired by Monte Carlo tree search (MCTS), yet it is improved with state merging capabilities. Performing merges allows us to evolve the tree model into a graph over time, as we periodically perform similarity tests borrowed from automata learning theory to learn states that are equivalent to one another. This results in improved efficiency and scalability over standard MCTS. Empirical results demonstrate orders of magnitude performance improvement over the state-of-the-art RL algorithms for RDPs. We discuss limitations both in concerning the MCTS implementation and similarity tests from probabilistic automata. © 2023 Copyright for this paper by its authors.

关键词： Reinforcement learning

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Design of Supervisory Model Predictive control for HVAC Systems and Two Zones with Consideration of Energy Efficiency and Thermal Comfort 23

Design of Supervisory Model Predictive Control for HVAC Syst...

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23rd International Conference on control, automation and Systems, ICCAS 2023

作者： Srisurapanon, Panithan Banjerdpongchai, David Chulalongkorn University Center of Excellence in Intelligent Control Automation for Process Systems Faculty of Engineering Department of Electrical Engineering Pathumwan Bangkok10330 Thailand

ISBN: (纸本)9788993215274

This paper presents the design of supervisory model predictive control for HVAC systems and two zones. The supervisory control (SC) is designed to find the optimal reference temperature of each zone. The design criteria consist of the total operating cost (TOC) and the thermal comfort cost (TCC). Then, the model predictive control (MPC) is designed to track the optimal reference signals. When SC and MPC are designed for two zones simultaneously, they are referred to centralized SC and centralized MPC. On the other hand, when SC and MPC are designed for two zones separately, they referred to decentralized SC and decentralized MPC. We then compare the results between the decentralized control and the centralized control. The trade-off curve shows that the performance of centralized control is better than that of decentralized control. In particular, centralized MPC improves the performance in tracking reference signals. Furthermore, TOC of centralized control is lower than that of decentralized control. It can be concluded that the centralized control is appropriate for two zones in terms of the tracking of reference and the electrical charge. © 2023 ICROS.

关键词： Model predictive control

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Secrecy Performance Review for IoT-based Cognitive Farming System

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Recent Patents on engineering 2024年第7期18卷 66-75页

作者： Chopra, Khyati Alam, M. Afshar Department of CSE Jamia Hamdard University New Dehli India University School of Automation and Robotics GGSIPU New Delhi110032 India Department of Computer Science and Engineering Jamia Hamdard University New Delhi110062 India

Smart farm management has complex challenges;therefore, there is a need to improve the overall adaptability, profitability, and environmental soundness of the farming systems. Agricultural production can be enhanced with the help of IoT-based cognitive tools. The rapid increase in IoT-based smart systems has raised critical concerns about efficiently utilizing the wireless spectrum. To drastically bring the improvement in the utilization of the wireless spectrum, cognitive radio (CR) has emerged as an effective solution. The inherent openness and broadcast nature of the wireless medium have given rise to many security issues in cooperative networks. Information-theoretic security or physical layer security (PLS) is evolved as an efficacious wireless prototype for reliable transmissions to avert the eavesdropper from expropriating transmittal data on the wireless connections. Security is the key factor in these networks as they are exposed and active in be-havior, thus, are susceptible to fraudulent activities. In this patent study, we investigated the performance of the CR system in terms of secrecy and also examined the system in terms of diversity receipt and selection of relay. The secrecy outcome of channel state information at the sender was also studied. The detrimental effects of fading in cooperative networks were also extensively discussed. Cooperative diversity was examined by deploying MRC and SC strategies at receptors. It has been deduced that CSI knowledge at the sender also has an eloquent concussion on the secrecy of the cognitive system. © 2024 Bentham Science Publishers.

关键词： Cognitive radio

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PID-F controlled LFC in a Two-Area Power System with Renewable Integration Using Metaheuristic Approaches

PID-F Controlled LFC in a Two-Area Power System with Renewab...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Can, Özay Izci, Davut Ekinci, Serdar Ghandour, Raymond Salman, Mohammad Department of Electronics and Automation Recep Tayyip Erdogan University Rize Turkey Department of Computer Engineering Batman University Batman Turkey College of Engineering and Technology American University of the Middle East Kuwait

ISBN: (纸本)9798331532611

As a result of the rising usage of renewable energy sources (RES) and the altering load profile, it is becoming increasingly difficult to strike a balance between production and demand. This is because renewable energy sources are becoming more prevalent. For this reason, it is of the utmost importance to put the process of load frequency control (LFC) into action. Taking this into consideration, the objective of this study is to optimize the adjustment of the parameters of the proportional-integral-derivative with filter (PID-F) controller for the LFC process in a two-area power system that consists of photovoltaic (PV) panels and wind energy systems simultaneously. During the past few years, a number of innovative algorithms have been developed. These algorithms include the mountain gazelle optimizer (MGO), the hippopotamus optimizer (HO), and the puma optimizer (PO). The parameters of the PID-F controller were determined with the help of these algorithms, which were applied accordingly. The findings of the simulation reveal that all three algorithms managed to achieve results that were successful and comparable to one another in the LFC process. These results were attained by all three algorithms. ©2024 IEEE.

关键词： Wind power

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