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arXiv 2024年

作者： Nasir, Ali Mekid, Samir Sawlan, Zaid Alsawafy, Omar Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Mechanical Engineering Department KFUPM Dhahran Saudi Arabia Mathematics Department KFUPM Dhahran Saudi Arabia Systems Engineering Department Dhahran Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia

This paper considers a distributed decision-making approach for manufacturing task assignment and condition-based machine health maintenance. Our approach considers information sharing between the task assignment and health management decision-making agents. We propose the design of the decision-making agents based on Markov decision processes. The key advantage of using a Markov decision process-based approach is the incorporation of uncertainty involved in the decision-making process. The paper provides detailed mathematical models along with the associated practical execution strategy. In order to demonstrate the effectiveness and practical applicability of our proposed approach, we have included a detailed numerical case study that is based on open source milling machine tool degradation data. Our case study indicates that the proposed approach offers flexibility in terms of the selection of cost parameters and it allows for offline computation and analysis of the decision-making policy. These features create and opportunity for the future work on learning of the cost parameters associated with our proposed model using artificial intelligence. © 2024, CC BY.

关键词： Optimization

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Estimating Wind Energy Potential: Advanced Smart Hybrid VAWT Analysis in Banjarmasin, Indonesia

Estimating Wind Energy Potential: Advanced Smart Hybrid VAWT...

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International Conference on Power engineering and Renewable Energy (ICPERE)

作者： Elysa Nensy Irawan Mei Miyagawa Maulana Putra Ken-Ichiro Yamashita Goro Fujita Functional Control Systems Shibaura Institute of Technology Tokyo Japan Department of Electrical Engineering Shibaura Institute of Technology Tokyo Japan Centre for Instrumentation Calibration and Engineering Indonesia Agency for Meteorology Climatology and Geophysics Jakarta Indonesia Department of Electrical Engineering Salesian Polytechnic Tokyo Japan

ISBN: (数字)9798331504694

ISBN: (纸本)9798331504700

This study explores the potential of smart hybrid Savonius-Darrieus wind turbines to optimize wind energy capture in Indonesia, a country with significant wind resources. With solar and wind energy leading the renewable energy transition, this research focuses on enhancing wind turbine efficiency in regions with variable wind speeds. The hybrid Savonius-Darrieus turbine integrates the complementary strengths of both turbine types, employing a solenoid mechanism to switch between modes and a filtering method to stabilize operation. Our results demonstrate that this innovative design significantly reduces mechanical wear and operational instability by minimizing unnecessary switching events. Testing in Banjarmasin, Indonesia, the daily average wind energy potential for the smart hybrid and conventional hybrid turbines is calculated to be 6.1 kWh and 4.7 kWh, respectively. This condition revealed that the smart hybrid turbine generates approximately 30.89% more power than conventional hybrid turbines, highlighting its superior adaptability to fluctuating wind conditions. The turbine's ability to maintain efficient energy capture across a wide range of wind speeds underscores its potential for broader application in diverse environmental settings.

关键词： Renewable energy sources Energy capture Wind energy Filtering Wind speed Switches Wind power generation Hybrid power systems Wind turbines Solenoids

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Renewable Power Generation Maximization for UAVs with Adaptive Sliding Mode control

Renewable Power Generation Maximization for UAVs with Adapti...

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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Khalid Alfuwail Ali Nasir Md Shafiullah Ayman Abdallah Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia Control & Instrumentation Engineering Department IRC Intelligent Manufacturing and Robotics (IRC-IMR) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia Control & Instrumentation Engineering Department IRC for Sustainable Energy Systems (IRC-SES) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia Aerospace Engineering Department IRC for Aviation & Space Exploration (IRC-ASE) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

The demand for efficient and Fuel consumption alternative renewable energy sources in the aviation sector has led to the exploration of advanced technologies such as Ram Air Turbines (RATs). RATs are critical in applications requiring power generation in emergency scenarios that may happen to un-manned aerial vehicles (UAVs). However, the primary challenge lies in optimizing the performance of the RATs, such as power output and operational stability, under varying and unpredictable wind conditions. Traditional control methods often fail to adapt to these dynamic environments. This paper underscores the necessity of utilizing a recurrent neural network (RNN) to detect uncertain wind turbine dynamics; a sliding mode control rule is created in the suggested controller to monitor the optimal turbine rotation speed. Next, an online update technique is developed to provide real-time weight updates for the RNN, enabling control over maximum power extraction. According to simulation results, the suggested controller outperforms a traditional control approach in tracking the optimal turbine rotation speed and extracting the most wind power from RATs by 13 times, even in severe nonlinearities and system uncertainties.

关键词： Renewable energy sources Uncertainty Recurrent neural networks Stability analysis Real-time systems Hardware Wind turbines Vehicle dynamics Sliding mode control Wind energy conversion

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A Resilient Consensus-Based Energy 5.0 Framework for Micro-Grids Under Ramp-Rate Constraints and Stochastic FDI Attacks

A Resilient Consensus-Based Energy 5.0 Framework for Micro-G...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Ijaz Ahmed Abdul Basit Muhammad Rehan Amjad Ali Muhammad Maaruf Muhammad Khalid Department of Electrical Engineering Pakistan Institute of Engineering and Applied Sciences (PIEAS) Islamabad Pakistan IRC for Sustainable Energy Systems King Fahd University of Petroleum & Minerals (KFUPM) Saudi Arabia Control & Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Electrical Engineering Department KFUPM Dhahran Saudi Arabia

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Distributed power allocation (DPA) in micro-grids (MGs) has a significant potential for attaining a cost effective and reliable solution of power dispatch. Considering the significant risks posed by cyber-attacks and system limitations to the MGs, it is important to develop resilient methods for an efficient DPA, which is valuable both in terms of theoretical understanding and practical application for energy 5.0 framework. This work addresses the DPA problem in MGs, specifically focusing on the economic dispatch (ED) for the generation side while taking into account ramp-rate limits (RRLs) and stochastic false-data injection (FDI) attacks. A consensus-based protocol has been developed by considering the information of the incremental costs of neighbouring generators and local power mismatch for a generation facility. A stochastic FDI attack at the shared information over the network has been accounted. The proposed technique guarantees robust (and resilient) convergence by providing a sufficient criterion under RRLs and stochastic FDI attacks. The proposed approach is based of the distributed ED framework, and convergence analysis has been performed via two Lyapunov functions. The convergence of total power mismatch and error in synchronization of incremental costs to bounded sets are ensured by the proposed approach. The presented framework achieves an efficient energy production cost. The network's robustness and resilience for the shared information of incremental cost of energy production units as the consensus variable are accounted. The simulation study for a set of five generators under stochastic FDI attacks and RRLs are provided which confirm the theoretical findings of the proposed scheme.

关键词： Costs Protocols Uncertainty Stochastic processes Production Robustness Generators

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Particle Swarm Optimization Tuned PID control of Hybrid Renewable Energy Based Multi-Area Power System

Particle Swarm Optimization Tuned PID Control of Hybrid Rene...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Muhammad Majid Gulzar Muhammad Shahab Adnan Shakoor Department of Control & Instrumentation Engineering Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

The hybrid power system combines renewable and conventional power plants, resulting in certain power quality issues such as longer settling times and increased transient contents. One of the most significant problems with such a hybrid system is frequency variations, which can affect the overall efficiency and reliability of the energy system. To address this concern, the Load Frequency controller (LFC) is used to sustain the system frequency within safe limits and ensure the efficient and reliable operation of the electric grid. The primary function of governing the oscillation of load is to adjust the power delivery and balance the load demand of the system to maintain a specific range of power output. This study tries to determine the best control approach for efficiently regulating system frequency and upholding a power balance in the presence of renewable energy sources. In this work, controllers such as Proportional Integral Derivative (PID), Genetic algorithm-PID (GA-PID), and Particle Swarm Optimization-PID (PSO-PID) are examined and studied to settle the load oscillation issue arising in a two-area energy generation system. Comparison of results obtained with the controllers are presented and summarized based on their settling time (T s ), maximum overshoot (%OS) oscillation, and steady-state error (SSE).

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Detection of Cracks in the Industrial System Using Adaptive Principal Component Analysis and Wavelet Denoising

Detection of Cracks in the Industrial System Using Adaptive ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Faizan-e-Mustafa Ijaz Ahmed Muhammad Maaruf Muhammad Khalid Pakistan Institute of Engineering and Applied Sciences (PlEAS) Islamabad Pakistan Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Electrical Engineering Department KFUPM Dhahran Saudi Arabia IRC for Sustainable Energy Systems KFUPM Dhahran Saudi Arabia

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

In evaluating industrial cyber-physical systems, there is an emerging inclination toward employing data-driven exploration techniques for the purpose of fault detecting and diagnosing typical procedural behaviors. The primary objective is to identify occurrences of typical behavior of the fundamental factors contributing to the aberrations. Multivariate statistical analysis, namely Principal Component Analysis (PCA), has con-siderable importance within the realm of research methodologies. This method is frequently employed in the context of outlier detection metrics, including the Hotelling $T^{2}$ statistic and the Squared Prediction Error (SPE), which are commonly utilized for fault identification purposes. The present work presents a novel and adaptable thresholding technique that utilizes a modified variant of the PCA with wavelet denoising. This method en-ables enhanced sensitivity and robustness to abnormalities while minimizing the occurrence of false alarms and missed detection rate. In this paper, the novel methodology employs a dynamic threshold that undergoes adjustments in accordance with the available data of the Hanoi University of Science and Technology ball-bearing experimental setup. The findings indicated that the novel strategy exhibited significantly more efficacy in identifying anomalies compared to the conventional technique. Moreover, it exhibited a reduced probability of producing erroneous alerts raising sensitivity and robustness for fault detection.

关键词： Fault diagnosis Process monitoring Sensitivity Adaptive systems Fault detection Noise reduction Wavelet analysis

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Pattern Recognition Method for Detecting engineering Errors on Technical Drawings

Pattern Recognition Method for Detecting Engineering Errors ...

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AI IoT Congress (AIIoT), World

作者： Rimma Dzhusupova Richa Banotra Jan Bosch Helena Holmströ m Olsson Department of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Instrumentation Control &#x0026 Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

Many organizations are looking for how to automate repetitive tasks to reduce manual work and free up resources for innovation. Machine Learning, especially Deep Learning, increases the chance of achieving this goal while working with technical documentation. Highly costly engineering hours can be saved, for example, by empowering the manual check with AI, which helps to reduce the total time for technical documents review. This paper proposes a way to substantially reduce the hours spent by process engineers reviewing P&IDs (Piping & instrumentation Diagrams). The developed solution is based on a deep learning model for analyzing complex real-life engineering diagrams to find design errors - patterns that are combinations of high-level objects. Through the research on an extensive collection of P&ID files provided by McDermott, we prove that our model recognizes patterns representing engineering mistakes with high accuracy. We also describe our experience dealing with class-imbalance problems, labelling, and model architecture selection. The developed model is domain agnostic and can be re-trained on various schematic diagrams within engineering fields and, as well, could be used as an idea for other researchers to see whether similar solutions could be built for different industries.

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Optimal swing motion control for single-rod brachiation robot *

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IFAC-PapersOnLine 2023年第2期56卷 6320-6325页

作者： Juraj Lieskovský Hijiri Akahane Jaroslav Bušek Ikuo Mizuuchi Tomáš Vyhlídal Department of Instrumentation and Control Engineering Faculty of Mechanical Engineering and CIIRC-Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Technická 4 Prague 6 16607 Czechia Department of Mechanical Systems Engineering Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei-city Tokyo Japan

This paper focuses on the optimal swing and rotation control of a single-rod brachiation robot by repositioning its center of gravity. First, a time-optimal control is proposed and analyzed. It utilizes impulses of force at the robot's zero-angle and the turning-angle positions to reposition the center of gravity. Then, a practical implementation that addresses force limits is proposed, in the form of a PD controller paired with input-output linearization which uses the optimal solution as a setpoint. Both control policies are validated through simulations as a preliminary step to laboratory validation on an assembled single-rod robot. Enhanced attention is paid to energy evolution during the swing and rotation of the robot, in particular to the energy pumping achieved by repositioning the center of gravity.

关键词： Single-link robot optimal swing nonlinear control brachiation

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Consensus and Phase Synchronization of Multi-agent systems using Adaptive Models

Consensus and Phase Synchronization of Multi-agent Systems u...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Muhammad Majid Gulzar Muhammad Munaward Adnan Shakoor Huma Tahreem Department of Control & Instrumentation Engineering Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical Engineering University of Central Punjab Lahore Pakistan

In this paper, an adaptive models for the consensus and phase synchronization of coupled oscillators have been implemented. By using these models, consensus can be achieved by using different graph topologies, in which agents are converged to their average velocity within the minimum number of iterations. Moreover, the phase synchronization of coupled oscillators interacting on connected graphs is also addressed. The synchronization shows that all coupled oscillators can synchronized their position and velocity with respect to neighboring agents. In the end, the simulations of consensus and phase synchronization validate the theoretical results.

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Robust Load Frequency control of Hybrid Power System

Robust Load Frequency Control of Hybrid Power System

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International Conference on control, Automation and Diagnosis (ICCAD)

作者： Muhammad Majid Gulzar Malik Muhammad Umar Mujahed Mohammad Al-Dhaifallah Department of Control & Instrumentation Engineering Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical Engineering University of Central Punjab Lahore Pakistan

In the modern world, with the rapid technological advancements in the field of electricity, innovative techniques are being employed to optimize electric power generation. These techniques involve a combination of conventional energy sources (coal, gas, etc.) with Renewable Energy Sources (RES) (PV, wind, etc.) to meet the electric power demands. Unfortunately, the intermittent nature of these RES has a detrimental effect on the system's power quality. To counter this issue, an efficient, intelligent, and advanced control method that employs a Model Predictive controller (MPC) in parallel with Fractional Order Proportional Integral controller (FOPI) is proposed for Load Frequency control (LFC) of the connected power system. With the help of this controller, an optimum solution for this problem is established in this study to enhance the power quality of the overall system by reducing the frequency fluctuations in the system. In the end, system responses to load changes have been analyzed and compared with those of state-of-the-art controllers like the Firefly Algorithm (FA) tuned PI, the Genetic Algorithm (GA) tuned PI, and MPC tuned PI to show the adequacy of the proposed controller.

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