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A Novel Class of Energy-Preserving Runge-Kutta Methods for the Korteweg-de Vries Equation

Numerical Mathematics(Theory,Methods and Applications) 2022年第3期15卷 768-792页

作者： Yue Chen Yuezheng Gong Qi Hong Chunwu Wang Department of Mathematics Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjing 211106China Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing 210023China

In this paper,we present a quadratic auxiliary variable approach to develop a new class of energy-preserving Runge-Kutta methods for the Korteweg-de Vries *** quadratic auxiliary variable approach is first proposed to reformulate the original model into an equivalent system,which transforms the energy conservation law of the Korteweg-de Vries equation into two quadratic invariants of the reformulated *** the symplectic Runge-Kutta methods are directly employed for the reformulated model to arrive at a new kind of time semi-discrete schemes for the original *** consistent initial conditions,the proposed methods are rigorously proved to maintain the original energy conservation law of the Korteweg-de Vries *** addition,the Fourier pseudo-spectral method is used for spatial discretization,resulting in fully discrete energy-preserving *** implement the proposed methods effectively,we present a very efficient iterative technique,which not only greatly saves the calculation cost,but also achieves the purpose of practically preserving *** numerical results are addressed to confirm the expected order of accuracy,conservative property and efficiency of the proposed algorithms.

关键词： Quadratic auxiliary variable approach symplectic Runge-Kutta scheme energypreserving algorithm Fourier pseudo-spectral method

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Arbitrarily High-Order Energy-Preserving Schemes for the Camassa-Holm Equation Based on the Quadratic Auxiliary Variable Approach

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Advances in Applied Mathematics and Mechanics 2023年第5期15卷 1233-1255页

作者： Yuezheng Gong Qi Hong Chunwu Wang Yushun Wang School of Mathematics Nanjing University of Aeronautics and AstronauticsNanjingJiangsu 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjingJiangsu 211106China Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems School of Mathematical SciencesNanjing Normal UniversityNanjingJiangsu 210023China

In this paper,we present a quadratic auxiliary variable(QAV)technique to develop a novel class of arbitrarily high-order energy-preserving algorithms for the Camassa-Holm *** QAV approach is first utilized to transform the original equation into a reformulated QAV system with a consistent initial *** the reformulated QAV system is discretized by applying the Fourier pseudo-spectral method in space and the symplectic Runge-Kutta methods in time,which arrives at a class of fully discrete *** the consistent initial condition,they can be rewritten as a new fully discrete system by eliminating the introduced auxiliary variable,which is rigorously proved to be energy-preserving and *** numerical experiments are conducted to confirm the expected order of accuracy,conservative property and efficiency of the proposed *** presented numerical strategy makes it possible to directly apply a special class of Runge-Kutta methods to develop energy-preserving algorithms for a general conservative system with any polynomial energy.

关键词： Camassa-Holm equation quadratic auxiliary variable high-order energy-preserving schemes symplectic Runge-Kutta methods

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Energy-Efficient Ant Colony Based LEACH Routing Algorithm in Wireless Sensor Network 4

Energy-Efficient Ant Colony Based LEACH Routing Algorithm in...

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4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022

作者： Abd Latif, Muhammad Zahir Lim, Kit Guan Tan, Min Keng Ee Chuo, Helen Sin Wang, Tienlei Kin Teo, Kenneth Tze Modelling Simulation & Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia Wuyi University Department of Intelligent Manufacturing Jiangmen China

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Wireless sensor network (WSN) is a network consist of multiple sensor nodes which sense and transmit data to a base station for data collection. Since the nodes in WSN are battery powered devices and nodes loss energy mostly due to transmission, an energy efficient routing protocol is needed to reduce the nodes energy consumption and prolong the network lifetime. However, existing routing protocols produce some drawbacks such as selection of cluster head with low residual energy and formation of different sizes of cluster which leads to uneven energy consumption among the nodes. Therefore, an Ant Colony Optimization based Low Energy Adaptive Clustering Hierarchy (LEACH-ACO) protocol for energy efficient transmission in WSN is proposed in this paper. This research aims to develop a routing protocol that utilize the existing LEACH routing protocol to improve the performance of WSN and prolong the lifetime of the network. The results showed that LEACH-ACO protocol outperformed Direct Transmission (DT) and LEACH protocol in terms of network lifetime, energy consumption and energy per transmission. © 2022 IEEE.

关键词： Ant colony optimization

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Multi-Area Load Frequency Control Using Particle Swarm Optimization

Multi-Area Load Frequency Control Using Particle Swarm Optim...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Min Keng Tan Wei Han Lim Kit Guan Lim Wei Yeang Kow Min Sian Ng Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

Load Frequency Control is indeed important in any country that operates an interconnected power grid for regulating system frequency by adjusting the generation to match the load demand. To maintain the power system stability and improve efficiency in scheduling, this paper proposes Two-area Load Frequency Control (LFC) Optimization with Particle Swarm Optimization. The design process begins with understanding the fundamental concepts, starting from Automotive Generation Control in a single-area power system design and progressing to LFC design in a two-area power system. The two-area power system consists of Tie-line Bias Control (TLBC) for maintaining zero tie-line power and Area Control Error (ACE) for stabilizing system frequency. To achieve fitness results in simulations, this paper presents three modeling designs: conventional design, controller design, and controller design with PSO. The controller system with PSO leads an evaluation of 53.4 % time schedule in system frequency performance and an evaluation of 76.9% time schedule in generation power deviation with respect to the conventional model. In addition, the controller system lags an evaluation of 70.0% time schedule in system frequency performance and an evaluation of a 78.7 % time schedule in generation power deviation with respect to the conventional model.

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Optimization of Photovoltaic Energy Harvesting Using Clonal Selection Algorithm

Optimization of Photovoltaic Energy Harvesting Using Clonal ...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Min Keng Tan Grace Butiza Joponi Kit Guan Lim Ahmad Razani Haron Chang-Yii Chai Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

The rising demand for renewable energy sources has fueled extensive research in photovoltaic (PV) systems. However, conventional Maximum Power Point Tracking (MPPT) algorithms often encounter challenges when tracking the global maximum power point under non-uniform irradiance conditions. To address this issue, the Clonal Selection Algorithm (CSA) is proposed as an effective approach to enhance MPPT algorithm performance. The CSA dynamically adjusts the voltage perturbation size based on instant ambient irradiance and temperature, leading to improved global maximum power point tracking and enhanced efficiency in PV systems. Experimental results demonstrate the superiority of the proposed CSA over conventional MPPT algorithms, especially in scenarios with varying solar irradiance. The CSA's adaptability allows PV systems to operate closer to their optimal efficiency, maximizing energy harvest from available solar resources. Overall, this research contributes valuable insights into sustainable and efficient energy solutions by leveraging the capabilities of the CSA. Successfully integrating the CSA in PV systems plays a critical role in establishing an eco-friendly and resilient renewable energy infrastructure, for a greener future.

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simulation and Batch modelling of Microbial Biosurfactant Production

Simulation and Batch Modelling of Microbial Biosurfactant Pr...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Helen Sin Ee Chuo Andy Raymond Ramlan Kit Guan Lim Min Keng Tan Hou Pin Yoong Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

This project concentrates on simulating the batch microbial biosurfactant production in crude oil and its interfacial tension response. Bacterial metabolism has been widely studied for its significant role in bioremediation of oil spill, which is proven capable of reducing the interfacial tension between oil and water. Therefore, this simulation is integrated to observe the metabolic behaviour of the bacteria of interest upon its uptake of carbon source from crude oil., biosurfactant production and the system's interfacial tension which are some of the outputs mainly being discussed within the culture system. The metabolic process in the crude oil batch is first modelled, then simulated in MATLAB software, and the results are verified through literature and process theories, while the model was validated using the experimental data. The simulation will use a step size of $\mathbf{1/60 \mathrm{h}\ .}$ equivalent to 60 seconds, set to a total of 11520 iterations for a running time of 8 days. Different crude oil substrate concentrations are set to $\mathbf{1.5 \mathrm{g}/\mathrm{L}, 2.0\mathrm{g}/\mathrm{L}, 2.5\mathrm{g}/\mathrm{L}, 3.0\mathrm{g}/\mathrm{L}}$ and $\mathbf{3.5 \mathrm{g}/\mathrm{L}}$ for parameter testing and the initial concentrations of biosurfactant and cell concentration are $\mathbf{0.02 \mathrm{g}/\mathrm{L}}$ and $\mathbf{0.02 \mathrm{g}/\mathrm{L}}$ respectively, while the initial interfacial tension is set at 70.8933 $\text{mN}/\mathrm{m}$ . The simulation outcome in this study signifies that the final concentrations of biosurfactant and bacteria cell increases with the increase in substrate concentration as crude oil degrades completely quicker with substrate concentration increase among culture batches obtained from the parameter testing. Additionally, the simulated interfacial tension profile plotted against biosurfactant from experimental research., showed similar profiles across batch cultures with an increasing substrate conce

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Distance Recognition Using QR Code Marker 6

Distance Recognition Using QR Code Marker

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6th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2024

作者： Lee, Ian Jian Yi Yoong, Hou Pin Teo, Kenneth Tze Kin Chai, Chang Yii Universiti Malaysia Sabah Biomechatronic Research Laboratory Faculty of Engineering Sabah Kota Kinabalu Malaysia Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia Universiti Malaysia Sabah High Voltage Power Energy Research Faculty of Engineering Sabah Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

Existing distance measuring technologies such as ultrasonic distance sensor and laser range finders are commercially viable but have considerable drawbacks together with significant advantages. There is no balanced distancing solution when factoring together cost, size, maximum range and minimum clearance. This study proposes an incremental distancing solution which could minimize the individual drawbacks of the current absolute distancing solutions while maintaining most of their advantages. The solution consists of a device with a camera and processor that is capable of capturing two distance markers in a single frame and decode the encoded information in the distance markers. This solution will provide measurement precision more than each individual marker can provide itself based on the resolution of the camera and also the length between the two markers in frame. QR codes will be used as the distance marker due to their widespread use, error correction and royalty-free standard. The distance markers will have to be placed at a fixed distance interval onto a measuring surface. Millimeter precision is possible based on the calculations performed and verified with experimental results. © 2024 IEEE.

关键词： Cameras

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Transmission path optimization Based on Efficiency Communication System

Transmission path optimization Based on Efficiency Communica...

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2022 International Symposium on Sensor Technology and Control, ISSTC 2022

作者： Fan, Jin Lim, Kit Guan Ee Chuo, Helen Sin Tan, Min Keng Farzamnia, Ali Teo, Kenneth Tze Kin Modelling Simulation and Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

Routing is the core of wireless sensor network deployment. This paper points out the research focus of the wireless sensor network transmission path and discusses the optimization problem of the transmission based on grid model. In this paper, routing attribute table that is maintained by the nodes, the density and relative distance of node distribution, is used to determine the clustering method. At the same time, the developed algorithm combines the relative position of the cluster and the base station to further improve the routing method of the sub-cluster head, Finally, the algorithm analyzes the influence of different parameters on the transmission path, and use the simulation experiments to evaluate the conclusions. © Published under licence by IOP Publishing Ltd.

关键词： Sensor nodes

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Optimization of Yeast Fermentation Process using Genetic Algorithm 3

Optimization of Yeast Fermentation Process using Genetic Alg...

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3rd IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2021

作者： Chuo, Helen Sin Ee Lo, Christine Yuh King Tan, Min Keng Tham, Heng Jin Kumaresan, Sivakumar Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

This paper proposes genetic algorithm (GA) to optimize the productivity of yeast fermentation process. The proposed optimizer aims to maximize yeast productivity while minimizing the by-product of ethanol. Various initial glucose concentrations will affect yeast productivity and influence the performance of yeast fermentation. Yeast has relatively high ethanol production as compared with other microorganisms. Since the excessive ethanol formation in the yeast fermentation process will have a negative impact on quality of the product, it is needed to optimize glucose feeding rate at optimal level for maximizing the yeast productivity. The conventional open-loop feeding system is inadequate to minimize the growth of byproduct as the system will not regulate the glucose feeding rate based on the instant needs. Thus, GA is proposed to optimize the glucose feeding profile based on the instant concentration of yeast, glucose, oxygen and ethanol inside the fermentation tank. The results show the proposed GA can obtain a higher yield production of 95.3% as compared to the conventional open-loop system with 92.5% yield production. The results reveal that the optimal glucose feeding rate using GA is achieved satisfyingly and successfully. © 2021 IEEE.

关键词： Genetic algorithms

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Advanced Fault Detection in DC Microgrid System using Reinforcement Learning 3

Advanced Fault Detection in DC Microgrid System using Reinfo...

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3rd IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2021

作者： Tan, Min Keng Lee, Kar Leong Lim, Kit Guan Haron, Ahmad Razani Ibrahim, Pungut Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

As technologies are expanding, the demand for power supply also increases. This causes the demand for power is difficult to be fulfilled as non-renewable sources are reducing. Therefore, the microgrid concept is introduced, where it is constructed with renewable energy sources, energy storage devices and loads. There are two types of microgrid, which are alternating current (AC) microgrid and direct current (DC) microgrid. Various research show that DC microgrid has more advantages over AC microgrid. However, DC microgrid is not widely used due to the lack of studies on it compared to AC microgrid. Besides, DC microgrid has one significant problem not fixed, which is the fault in the DC microgrid. Whenever a fault occurs, the whole DC microgrid will be affected rapidly. Therefore, this project aims to design a fault detector based on artificial intelligence to detect the fault and isolate the fault effectively. A fault detector based artificial intelligence should be implemented into the DC microgrid system to protect it. Two techniques in Artificial Immune System are being compared. The results showed that the improved Negative Selection Algorithm with variable sized detector has better performance than the general Negative Selection Algorithm with constant sized radius in detecting fault in DC microgrid system. © 2021 IEEE.

关键词： Reinforcement learning

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