Path tracking control is a fundamental technology in autonomous vehicle applications, but it faces significant challenges related to vehicle modeling and external disturbances. In this paper, an improved model-free ad...
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ISBN:
(数字)9798331521950
ISBN:
(纸本)9798331521967
Path tracking control is a fundamental technology in autonomous vehicle applications, but it faces significant challenges related to vehicle modeling and external disturbances. In this paper, an improved model-free adaptive control strategy, leveraging data-driven approaches and gradient descent parameter optimization, is proposed. First, an enhanced lineofsight method is used to generate the desired heading angle, simplifying the multi-dimensional path tracking problem into a more manageable heading angle tracking task. Then, the gradient descent model-free adaptive control strategy is applied, with the core idea of incorporating the gradient descent algorithm in the controller's time-varying parameter update process to achieve optimal control. The effectiveness of the proposed algorithm is validated through simulations, demonstrating its robustness in nonlinear systems and path tracking control scenarios. Comparative analysis with model-based methods highlights the superior stability and adaptability of the approach.
We propose to employ hazard labels to communicate a robot's potentially hazardous capabilities and behaviours to users. Robots can pose a range of ethical and physical safety concerns that users must be aware of w...
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ISBN:
(数字)9798350378931
ISBN:
(纸本)9798350378948
We propose to employ hazard labels to communicate a robot's potentially hazardous capabilities and behaviours to users. Robots can pose a range of ethical and physical safety concerns that users must be aware of when deciding whether to interact. We developed an initial set of key hazards, and a corresponding prototype of a hazard labeling scheme, to demonstrate the potential of this approach. We intend to use this prototype to support exploration of different styles of labeling, and ultimately to develop a more formalized system of robot hazard communication.
The aim of this paper is to analyze the achievable rate in the power domain non-orthogonal multiple access (NOMA) technique for communication between six devices through an Internet-of-Things (IoT) gateway device. In ...
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ISBN:
(数字)9798331520762
ISBN:
(纸本)9798331520779
The aim of this paper is to analyze the achievable rate in the power domain non-orthogonal multiple access (NOMA) technique for communication between six devices through an Internet-of-Things (IoT) gateway device. In this study, we first derive the expressions for the Signal-to-Noise Ratio (SNR) and Signal-to-interference-plus-noise ratio (SINR) for the transmission between the devices, which are crucial to determine the overall system performance. The analysis also takes into account the impact of co-channel interference (CCI) at the relay node, a significant factor that affects communication reliability in NOMA systems. Furthermore, we investigate how various system parameters such as distance, transmit power, and path loss exponent influence the achievable rate, considering the dynamic nature of wireless environments. By optimizing power allocation and addressing the challenges of interference, the system can achieve higher throughput and improved reliability. This paper aims to provide a comprehensive understanding of the performance of NOMA in the context of IoT system framework, offering insights into the trade-offs involved in achieving high data rates while ensuring energy efficiency. The results are discussed in terms of the systems' response to changes in key parameters, with the goal of optimizing performance for practical IoT deployments.
As society progresses, the significance of power distribution in maintaining the reliability of the power system becomes increasingly paramount. Over time, experts have realized that the outdated load control method i...
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ISBN:
(数字)9798331521950
ISBN:
(纸本)9798331521967
As society progresses, the significance of power distribution in maintaining the reliability of the power system becomes increasingly paramount. Over time, experts have realized that the outdated load control method is inadequate in fulfilling current demands. Consequently, distributed load control algorithm has garnered considerable attention from academic circles. The research presents a distributed convex optimization load control algorithm, which promises fixed-time convergence and decreased overall system costs for economic dispatch, provided that a balance between demand and supply is maintained. When the initial states are constrained, the fixed-time algorithm can be substantiated under the fixed-time stability theory. Ultimately, simulations are employed to validate the effectiveness of the proposed algorithm.
Novel controllers have been introduced in energy systems to enhance efficiency and manage uncertainties in renewable sources. These controllers incorporate real-time meteorological and SCADA data for more accurate win...
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ISBN:
(数字)9798331521165
ISBN:
(纸本)9798331521172
Novel controllers have been introduced in energy systems to enhance efficiency and manage uncertainties in renewable sources. These controllers incorporate real-time meteorological and SCADA data for more accurate wind turbine output predictions. This paper presents a curtailment weighting control module using a CNN-BiLSTM model trained on data from the Dongbok wind farm. The objective is to minimize active power loss during curtailment using a sequential quadratic programming algorithm, focusing on improving prediction accuracy and operational efficiency. The system integrates a real-time simulation environment, including hardware-in-the-loop simulation. Communication between wind farm controllers, RTDS grid models, and the management system is via the Modbus TCP/IP protocol. Comparative analysis with traditional methods validates the proposed method's advantages. Real-time simulation results indicate that the curtailment weighting control module reduces power losses and improves operational efficiency. The proposed method achieved a power loss reduction of 2.5813 kWh compared to traditional PD control methods and demonstrated a 99.9% availability across all wind turbines during curtailment scenarios. This study highlights the importance of combining machine learning-based control with advanced strategies to address challenges in renewable energy integration and maintain a stable power supply.
technology is a cornerstone of modern life, yet the software engineering field struggles to reflect the diversity of contemporary society. This lack of diversity and inclusivity within the software industry can be tra...
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ISBN:
(数字)9798331535100
ISBN:
(纸本)9798331535117
technology is a cornerstone of modern life, yet the software engineering field struggles to reflect the diversity of contemporary society. This lack of diversity and inclusivity within the software industry can be traced back to limited representation in software engineering academic settings, where students from underrepresented groups are often stigmatized despite the field's rich history of contributions from scientists from diverse backgrounds. Over the years, studies have revealed that women, LGBTQIA+ individuals, and Black students frequently encounter unwelcoming environments in software engineering programs. However, similar to other fields, increasing awareness of notable individuals from marginalized backgrounds could inspire students and foster a more inclusive environment. This study reports the findings from a replicated global survey with undergraduate software engineering students, exploring their knowledge of distinguished scientists from underrepresented groups. These findings show that students have limited awareness of these figures and their contributions, highlighting the need to improve diversity awareness and develop educational practices that celebrate the achievements of historically marginalized groups in software engineering.
Medical Cyber-Physical systems (MCPS) are essential in modern healthcare, enabling real-time patient monitoring, diagnosis, and treatment. However, their integration of digital and physical elements exposes them to cy...
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ISBN:
(数字)9798331529833
ISBN:
(纸本)9798331529840
Medical Cyber-Physical systems (MCPS) are essential in modern healthcare, enabling real-time patient monitoring, diagnosis, and treatment. However, their integration of digital and physical elements exposes them to cyber-attacks, threatening both patient safety and data integrity. This paper shows a novel cybersecurity framework that combines blockchain technology and deep learning-based intrusion detection to protect MCPS. The proposed model uses a deep DNN-based intrusion detection system (IDS) to categorize medical data as either normal or malicious. Blockchain technology is incorporated to ensure secure, tamper-proof, and decentralized storage of patient information. To improve detection accuracy and reduce false positives, feature fusion techniques, processed through convolutional neural networks (CNNs), are applied. Ethereum-based blockchain ensures that medical data remains confidential and resistant to unauthorized alterations. The system’s effectiveness is validated using a healthcare dataset, showing a marked improvement in detection accuracy, precision, and recall over traditional methods. This integrated solution strengthens the safety and reliability of MCPS, protecting patient data while maintaining efficient data shared between medical devices and healthcare networks. Future research will focus on real-time applications and scaling the model for larger healthcare systems.
system and software design benefits greatly from formal modeling, allowing for automated analysis and verification early in the design phase. Current methods excel at checking information flow and component interactio...
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ISBN:
(数字)9798331508180
ISBN:
(纸本)9798331508197
system and software design benefits greatly from formal modeling, allowing for automated analysis and verification early in the design phase. Current methods excel at checking information flow and component interactions, ensuring consistency, and identifying dependencies within systems Modeling Language (SysML) models. However, these approaches often lack the capability to perform physics-based reasoning about a system's behavior represented in SysML models, particularly in the electromechanical domain. This significant gap critically hinders the ability to automatically and effectively verify the correctness and consistency of the model's behavior against well-established underlying physical principles. Therefore, this paper presents an approach that leverages existing research on function representation, including formal languages, graphical representations, and reasoning algorithms, and integrates them with physics-based verification techniques. Four case studies (coffeemaker, vacuum cleaner, hairdryer, and wired speaker) are inspected to illustrate the model's practicality and effectiveness in performing physics-based reasoning on systems modeled in SysML. This automated physics-based reasoning is broken into two main categories: (i) structural, which is performed on BDD and IBD, and (ii) functional, which is then performed on activity diagrams. This work advances the field of automated reasoning by providing a framework for verifying structural and functional correctness and consistency with physical laws within SysML models.
This study integrates the Time-to-Collision (TTC) control strategy. Utilizing the PC-Crash software, we have constructed a simulation model tailored for motor vehicle-cyclist collision scenarios. With the survival rat...
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This paper investigates reliability and control of an Industrial Micro-Grid (IMG) system engaged to provide uninterrupted and quality power to export-oriented industries in Chattogram Export Processing Zone (CEPZ) and...
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ISBN:
(数字)9798350357509
ISBN:
(纸本)9798350357516
This paper investigates reliability and control of an Industrial Micro-Grid (IMG) system engaged to provide uninterrupted and quality power to export-oriented industries in Chattogram Export Processing Zone (CEPZ) and Karnaphuli Export Processing Zone (KEPZ). The uninterrupted and reliable power supply is crucial for the operation of these industries within CEPZ and KEPZ, which collectively demand a maximum of 100 MW out of which 72 MW is made available from its internal power generating source and additional 28 MW is sourced from the regional national power grid. Despite the demand for uninterrupted power, frequent tripping of this IMG due to various faults originating from consumer ends has posed a significant challenge for its trusted reliability. To mitigate this issue within a tolerable limit, a tactful solution called Generating Bus Splitting (GBS) was proposed. It involves the dis-integrating and relocating of one of the master feeders from its Central Generation Bus (CGB) to rationally distribute fault burden concentration. This model offers several advantages, including grid shifting loss reduction, improved grid dispatch, mainly contributing to the enhancing IMG reliability by reducing its total blackout, and enhanced emergency power interruption handling capabilities.
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