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Adaptive Nonlinear PD Controller of Two-Wheeled Self-Balancing Robot with External Force

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Computers, Materials & Continua 2024年第11期81卷 2337-2356页

作者： Van-Truong Nguyen Dai-Nhan Duong Dinh-hieu Phan thanh-Lam bui Xiem HoangVan Phan Xuan Tan Faculty of Mechatronics SMAEHanoi University of IndustryHanoi159999Vietnam Faculty of Electronics and Telecommunications Vietnam National University-University of Engineering and Technology(VNU-UET)Hanoi10000Vietnam College of Engineering Shibaura Institute of TechnologyTokyo135-8548Japan

This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external *** proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error *** addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control *** proposed controller is basic in design yet simple to *** ANPD controller has the advantage of being computationally lightweight and providing high robustness against external *** stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its *** and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed *** proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control *** represents a promising solution for applications requiring precise and stable motion control under varying external conditions.

关键词： Two-wheeled self-balancing robot nonlinear PD control external force genetic algorithm

Complex Network Analysis of the Robustness of the Hanoi, Vietnam Bus Network

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Journal of Systems Science & Complexity 2019年第5期32卷 1251-1263页

作者： TRAN Vu hieu CHEONG Siew Ann bui Ngoc Dung Faculty of Information Technology University of Transport and CommunicationsHanoiVietnam Division of Physics and Applied Physics School of Physical and Mathematical SciencesNanyang Technological University21 Nanyang Link637371Singapore Faculty of Information Technology University of Transport and CommunicationsHanoiVietnam.

Many complex networks exist to facilitate the transport of material or information. In this capacity, the authors are often concerned with the continued flow of material or information when a fraction of the links in the complex network is disrupted. In other words, the authors are interested in the robustness of the complex network. In this paper, the authors survey measures of robustness like the average path length, the average clustering coefficient, the global efficiency, the size of largest cluster and use these to analyze the robustness of the bus network in Hanoi, Vietnam. The authors find that the bus network is robust against random failure but sensitive to targeted attack, in agreement with its scale-free character. By examining sharp drops in the average path length within the largest cluster of the Hanoi bus network under successive targeted attack, the authors identify five nodes whose loss lead to the fragmentation of the network into five or six disconnected clusters. These isolated clusters represent geographically the Central, Western, Southern, and Northwestern districts of Hanoi. Special considerations must therefore be given to these five nodes when planners wish to expand the bus network, or make it more robust.

关键词： Complex network hanoi bus network random failure robustness targeted attack

Novel Soft ComputingModel for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on the Bagging and Sibling of Extra Trees Models

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Computer Modeling in Engineering & Sciences 2023年第3期134卷 2227-2246页

作者： Quang-hieu Tran Hoang Nguyen Xuan-Nam bui Department of Surface Mining Mining FacultyHanoi University of Mining and GeologyHanoi100000Vietnam Innovations for Sustainable and Responsible Mining(ISRM)Research Group Hanoi University of Mining and GeologyHanoi100000Vietnam

This study considered and predicted blast-induced ground vibration(PPV)in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning ***,four machine learning algorithms,including support vector regression(SVR),extra trees(ExTree),K-nearest neighbors(KNN),and decision tree regression(DTR),were used as the base models for the purposes of combination and PPV initial *** bagging regressor(BA)was then applied to combine these base models with the efforts of variance reduction,overfitting elimination,and generating more robust predictive models,abbreviated as BA-ExTree,BAKNN,BA-SVR,and *** is emphasized that the ExTree model has not been considered for predicting blastinduced ground vibration before,and the bagging of ExTree is an innovation aiming to improve the accuracy of the inherently ExTree model,as *** addition,two empirical models(i.e.,USBM and Ambraseys)were also treated and compared with the bagging models to gain a comprehensive *** this aim,we collected 300 blasting events with different parameters at the Sin Quyen copper mine(Vietnam),and the produced PPV values were also *** were then compiled as the dataset to develop the PPV predictive *** results revealed that the bagging models provided better performance than the empirical models,except for the BA-DTR *** those,the BA-ExTree is the best model with the highest accuracy(i.e.,88.8%).Whereas,the empirical models only provided the accuracy from 73.6%–76%.The details of comparisons and assessments were also presented in this study.

关键词： Mine blasting blast-induced ground vibration environmentally friendly blasting peak particle velocity bagging extra trees

Atomistic simulation of free transverse vibration of graphene,hexagonal SiC, and BN nanosheets

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Acta Mechanica Sinica 2017年第1期33卷 132-147页

作者： Danh-Truong Nguyen Minh-Quy Le thanh-Lam bui Hai-Le bui School of Mechanical Engineering Hanoi University of Science and Technology Hanoi 10000 Vietnam International Institute for Computational Science and Engineering Hanoi University of Science and TechnologyHanoi 10000 Vietnam Faculty of Mechanical Engineering Hanoi University of Industry Hanoi 10000 Vietnam

Free transverse vibration of monolayer graphene, boron nitride (BN), and silicon carbide (SiC) sheets is investigated by using molecular dynamics finite element method. Eigenfrequencies and eigenmodes of these three sheets in rectangular shape are studied with different aspect ratios with respect to various boundary conditions. It is found that aspect ratios and boundary conditions affect in a similar way on natural frequencies of graphene, BN, and SiC sheets. Natural frequencies in all modes decrease with an increase of the sheet’s size. Graphene exhibits the highest natural frequencies, and SiC sheet possesses the lowest ones. Missing atoms have minor effects on natural frequencies in this study.

关键词： Atomistic simulation Hexagonal sheet Transverse vibration Molecular dynamics finite element method

A Simplified Approach of Open Boundary Conditions for the Smoothed Particle Hydrodynamics Method

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Computer Modeling in Engineering & Sciences 2021年第11期129卷 425-442页

作者： thanh Tien bui Yoshihisa Fujita Susumu Nakata Graduate School of Information Science and Engineering Ritsumeikan UniversityShiga525-8577Japan College of Information Science and Engineering Ritsumeikan UniversityShiga525-8577Japan

In this paper,we propose a simplified approach of open boundary conditions for particle-based fluid simulations using the weakly compressible smoothed-particle hydrodynamics(SPH)*** this scheme,the values of the inflow/outflow particles are calculated as fluid particles or imposed desired values to ensure the appropriate evolution of the flow field instead of using a renormalization process involving the fluid *** concentrate on handling the generation of new inflow particles using several simple approaches that contribute to the flow field *** advantages of theδ^(+).-SPH scheme,specifically the particle shifting technique,were successfully applied to correct the position,velocity,and pressure terms of the ***,unexpected errors were removed and tensile instabilities of the particles were *** proposed technique is validated for several benchmark test cases,and the tests show that the results match the reference solutions well.A viscous open-channel flow is used to demonstrate the stability of the flow field during the computational *** on this stability,we compress the computational domain to a lower resolution in a second test case while preserving the accuracy of the *** over a backward-facing step is used to highlight the challenges of inflow boundary conditions with prescribed or non-prescribed *** developed technique is well suited to the wall boundaries and the evolution of the flow *** results demonstrate the robustness and versatility of the proposed technique for a variety of simulations.

关键词： Fluid simulation smoothed particle hydrodynamics open boundaries

A hierarchical system to predict behavior of soil and cantilever sheet wall by data-driven models

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Frontiers of Structural and Civil Engineering 2022年第6期16卷 667-684页

作者： Nang Duc bui hieu Chi PHAN Tiep Duc PHAM Ashutosh Sutra DHAR Institute of Techniques for Special Engineering Le Quy Don Technical UniversityHanoi 100000Vietnam Faculty of Engineering and Applied Science Memorial University of NewfoundlandSt.John’sNL A1B 3X5Canada

The study proposes a framework combining machine learning(ML)models into a logical hierarchical system which evaluates the stability of the sheet wall before other *** study uses the hardening soil(HS)model to develop a 200-sample finite element analysis(FEA)database,to develop the ML ***,a system containing three trained ML models is proposed to first predict the stability status(random forest classification,RFC)followed by 1)the cantilever top horizontal displacement of sheet wall(artificial neural network regression models,RANN1)and 2)vertical settlement of soil(RANN2).The uncertainty of this data-driven system is partially investigated by developing 1000 RFC models,based on the application of random sampling technique in the data splitting *** on the distribution of the evaluation metrics reveals negative skewed data toward the 1.0000 *** implies a high performance of RFC on the database with medians of accuracy,precision,and recall,on test set are 1.0000,1.0000,and 0.92857,*** regression ANN models have coefficient of determinations on test set,as high as 0.9521 for RANN1,and 0.9988 for RANN2,*** parametric study for these regressions is also provided to evaluate the relative insight influence of inputs to output.

关键词： finite element analysis cantilever sheet wall machine learning artificial neural network random forest

Occurrence of microcystins in water,sediment,and aquatic animals in Dau Tieng Reservoir,Vietnam

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Journal of Oceanology and Limnology 2024年第6期42卷 1751-1763页

作者： thanh Luu PHAM Manh Ha bui Tan Duc NGUYEN thanh Son DAO Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh City 700000Vietnam Faculty of Environment Saigon UniversityHo Chi Minh City 700000Vietnam Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention and Guangdong Provincial Key Laboratory of Marine BiotechnologyShantou UniversityShantou 515063China Faculty of Environment and Natural Resources Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam Asian Center for Water Research(Centre Asiatique de Recherchesur l’Eau CARE)Ho Chi Minh City University of Technology(HCMUT)Vietnam National UniversityHo Chi Minh City 700000Vietnam

This study investigates the variations of microcystins(MCs)in water,cyanobacterial blooms,sediment,and aquatic organisms collected from the Dau Tieng Reservoir(DTR).*** liquid chromatography(HPLC)was employed to measure MC concentrations in various target *** indicate that Microcystis *** as the primary MC producer in the *** average concentrations of analyzed MCs in surface water ranged from 1.10 to 5.54μg/L,temporally and *** sediment,average concentrations varied from 0.15 to 1.13μg/g wet weight(WW)temporally and from 0.41 to 0.72μg/g WW *** were detected in different organs of fish species(Oreochromis *** Labiobarbus sp.)and in the entire soft tissues of bivalve(Corbicula sp.)and gastropod(Assiminea sp.).The highest observed MC concentration in July was 0.83±0.22μg/g WW in the intestines of fish Oreochromis *** presence of MCs in grass shrimp Palaemonetes *** observed solely in June,reaching a concentration of 0.28±0.19μg/g *** is the first report of MC accumulation in the grass shrimp Palaemonetes *** field *** the bivalve Corbicula sp.,the presence of analyzed MCs was consistent throughout the study period,except for March and September,with the highest concentrations in July at 0.77±0.1μg/g *** correlation analysis revealed significant positive correlations between MCs in water and sediment with MC concentrations in aquatic animals,indicating the potential transfer of MCs across different trophic *** estimated daily intake values for analyzed MCs indicate that fish collected from the DTR are considered safe for consumption,as long as only the edible organs,such as the muscle,are ***,bivalves or gastropods collected from the DTR are not safe for human *** study underscored the importance of monitoring MC accumulation in aquatic animals used as food to mitigate adverse effects on human health.

关键词： aquatic animal bioaccumulation cyanotoxin health risk toxic cyanobacteria

Simulation of cohesive crack growth by a variable-node XFEM

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Frontiers of Structural and Civil Engineering 2020年第1期14卷 215-228页

作者： Weihua FANG Jiangfei WU Tiantang YU thanh-Tung NGUYEN Tinh Quoc bui Nanjing Automation Institute of Water Conservancy and Hydrology Nanjing 210012China Department of Engineering Mechanics Hohai UniversityNanjing 211100China Laboratory of Solid Structures University of LuxembourgLuxembourg L-1359Luxembourg Institute for Research and Development Duy Tan UniversityDa Nang City 550000Vietnam Department of Civil and Environmental Engineering Tokyo Institute of TechnologyTokyo 152-8552Japan

A new computational approach that combines the extended finite element method associated with variable-node elements and cohesive zone model is *** using a new enriched technique based on sign function,the proposed model using 4-node quadrilateral elements can eliminate the blending element *** also allows modeling the equal stresses at both sides of the crack in the crack-tip as assumed in the cohesive model,and is able to simulate the arbitrary crack-tip *** multiscale mesh technique associated with variable-node elements and the arc-length method further improve the efficiency of the developed *** performance and accuracy of the present approach are illustrated through numerical experiments considering both mode-I and mixed-mode fracture in concrete.

关键词： extended finite element method cohesive zone model sign function crack propagation

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi bui Dam Duc Nguyen Hiep Van Le Indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning