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Dr. Van-Van Huynh
Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

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Research Keywords & Expertise

0 Adaptive Control
0 power system
0 Sliding mode control
0 load frequency control
0 interconnected system

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Sliding mode control
power system
load frequency control
Second order sliding mode control
interconnected system

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Journal article
Published: 29 March 2021 in Applied Sciences
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To provide a more practical method of controlling the frequency and tie-line power flow of a multi-area interconnected power system (MAIPS), a state observer based on sliding mode control (SOboSMC) acting under a second-order time derivative is proposed. The proposed design is used to study load frequency control against load disturbance, matched and mismatched uncertainty and parameter measurement difficulties of power systems that exist in the modern power plant, such as multi-area systems integrated with wind plants. Firstly, the state observer is designed to optimally estimate system state variables. The estimated states are applied to construct the model of the MAIPS. Secondly, a SOboSMC is designed with an integral switching surface acting on the second-order time derivative to forcefully drive the dynamic errors to zero and eliminate chattering, which can occur in the first-order approach to sliding mode control. In addition, the stability of the total power system is demonstrated with the Lyapunov stability theory based on a new linear matrix inequality (LMI) technique. To extend the validation of the proposed design control for practical purposes, it was tested in a New England system with 39 bus power against random load disturbances. The simulation results confirm the superiority of the proposed SOboSMC over other recent controllers with respect to overshoot and settling time.

ACS Style

Van Huynh; Bui Minh; Emmanuel Amaefule; Anh-Tuan Tran; Phong Tran; Van-Duc Phan; Viet-Thanh Pham; Tam Nguyen. Load Frequency Control for Multi-Area Power Plants with Integrated Wind Resources. Applied Sciences 2021, 11, 3051 .

AMA Style

Van Huynh, Bui Minh, Emmanuel Amaefule, Anh-Tuan Tran, Phong Tran, Van-Duc Phan, Viet-Thanh Pham, Tam Nguyen. Load Frequency Control for Multi-Area Power Plants with Integrated Wind Resources. Applied Sciences. 2021; 11 (7):3051.

Chicago/Turabian Style

Van Huynh; Bui Minh; Emmanuel Amaefule; Anh-Tuan Tran; Phong Tran; Van-Duc Phan; Viet-Thanh Pham; Tam Nguyen. 2021. "Load Frequency Control for Multi-Area Power Plants with Integrated Wind Resources." Applied Sciences 11, no. 7: 3051.

Research article
Published: 20 March 2021 in Complexity
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Nowadays, the power systems are getting more and more complicated because of the delays introduced by the communication networks. The existence of the delays usually leads to the degradation and/or instability of power system performance. On account of this point, the traditional load frequency control (LFC) approach for power system sketches a destabilizing impact and an unacceptable system performance. Therefore, this paper proposes a new LFC based on adaptive integral second-order sliding mode control (AISOSMC) approach for the large-scale power system with communication delays (LSPSwCD). First, a new linear matrix inequality is derived to ensure the stability of whole power systems using Lyapunov stability theory. Second, an AISOSMC law is designed to ensure the finite time reachability of the system states. To the best of our knowledge, this is the first time the AISOSMC is designed for LFC of the LSPSwCD. In addition, the report of testing results presents that the suggested LFC based on AISOSMC can not only decrease effectively the frequency variation but also make successfully less in mount of power oscillation/fluctuation in tie-line exchange.

ACS Style

Anh-Tuan Tran; Bui Le Ngoc Minh; Phong Thanh Tran; Van Van Huynh; Van-Duc Phan; Viet-Thanh Pham; Tam Minh Nguyen. Adaptive Integral Second-Order Sliding Mode Control Design for Load Frequency Control of Large-Scale Power System with Communication Delays. Complexity 2021, 2021, 1 -19.

AMA Style

Anh-Tuan Tran, Bui Le Ngoc Minh, Phong Thanh Tran, Van Van Huynh, Van-Duc Phan, Viet-Thanh Pham, Tam Minh Nguyen. Adaptive Integral Second-Order Sliding Mode Control Design for Load Frequency Control of Large-Scale Power System with Communication Delays. Complexity. 2021; 2021 ():1-19.

Chicago/Turabian Style

Anh-Tuan Tran; Bui Le Ngoc Minh; Phong Thanh Tran; Van Van Huynh; Van-Duc Phan; Viet-Thanh Pham; Tam Minh Nguyen. 2021. "Adaptive Integral Second-Order Sliding Mode Control Design for Load Frequency Control of Large-Scale Power System with Communication Delays." Complexity 2021, no. : 1-19.

Journal article
Published: 07 February 2021 in Energies
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In multi-area interconnected power systems (MAIPS), the measurement of all system states is difficult due to the lack of a sensor or the fact that it is expensive to measure. In order to solve this limitation, a new load frequency controller based on the second-order sliding mode is designed for MAIPS where the estimated state variable is used fully in the sliding surface and controller. Firstly, a model of MAIPS integrated with disturbance is introduced. Secondly, an observer has been designed and used to estimate the unmeasured variables with disturbance. Thirdly, a new second-order sliding mode control (SOSMC) law is used to reduce the chattering in the system dynamics where slide surface and sliding mode controller are designed based on system states observer. The stability of the whole system is guaranteed via the Lyapunov theory. Even though state variables are not measured, the experimental simulation results show that the frequency remains in the nominal range under load disturbances, matched and mismatched uncertainties of the MAIPS. A comparison to other controllers illustrates the superiority of the highlighted controller designed in this paper.

ACS Style

Anh-Tuan Tran; Bui Minh; Van Huynh; Phong Tran; Emmanuel Amaefule; Van-Duc Phan; Tam Nguyen. Load Frequency Regulator in Interconnected Power System Using Second-Order Sliding Mode Control Combined with State Estimator. Energies 2021, 14, 863 .

AMA Style

Anh-Tuan Tran, Bui Minh, Van Huynh, Phong Tran, Emmanuel Amaefule, Van-Duc Phan, Tam Nguyen. Load Frequency Regulator in Interconnected Power System Using Second-Order Sliding Mode Control Combined with State Estimator. Energies. 2021; 14 (4):863.

Chicago/Turabian Style

Anh-Tuan Tran; Bui Minh; Van Huynh; Phong Tran; Emmanuel Amaefule; Van-Duc Phan; Tam Nguyen. 2021. "Load Frequency Regulator in Interconnected Power System Using Second-Order Sliding Mode Control Combined with State Estimator." Energies 14, no. 4: 863.

Journal article
Published: 24 January 2021 in Electronics
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This paper centers on the design of highly robust observer sliding mode (HROSM)-based load frequency and tie-power control to compensate for primary frequency control of multi-area interconnected power systems integrated with renewable power generation. At first, the power system with external disturbance is model in the state space form. Then the state observer is used to estimate the system states which are difficult or expensive to measure. Secondly, the sliding mode control (SMC) is designed with a new single phase sliding surface (SPSS). In addition, the whole system asymptotic stability is proven with Lyapunov stability theory based on the linear matrix inequality (LMI) technique. The new SPSS without reaching time guarantees rapid convergence of high transient frequency, tie-power change as well as reduces chattering without loss of accuracies. Therefore, the superiority of modern state-of-the-art SMC-based frequency controllers relies on good practical application. The experimental simulation results on large interconnected power systems show good performance and high robustness against external disturbances when compared with some modern state of art controllers in terms of overshoots and settling time.

ACS Style

Van Huynh; Bui Minh; Emmanuel Amaefule; Anh-Tuan Tran; Phong Tran. Highly Robust Observer Sliding Mode Based Frequency Control for Multi Area Power Systems with Renewable Power Plants. Electronics 2021, 10, 274 .

AMA Style

Van Huynh, Bui Minh, Emmanuel Amaefule, Anh-Tuan Tran, Phong Tran. Highly Robust Observer Sliding Mode Based Frequency Control for Multi Area Power Systems with Renewable Power Plants. Electronics. 2021; 10 (3):274.

Chicago/Turabian Style

Van Huynh; Bui Minh; Emmanuel Amaefule; Anh-Tuan Tran; Phong Tran. 2021. "Highly Robust Observer Sliding Mode Based Frequency Control for Multi Area Power Systems with Renewable Power Plants." Electronics 10, no. 3: 274.

Journal article
Published: 09 December 2020 in Energies
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The implementation of the sliding mode control (SMC) for load frequency control of power networks becomes difficult due to the chattering phenomenon of high-frequency switching. This chattering problem in SMC is extremely dangerous for actuators used in power systems. In this paper, a continuous control strategy by combining a second-order mode and integral siding surface is proposed as a possible solution to this problem. The proposed second-order integral sliding mode control (SOISMC) law not only rejects chattering phenomenon in control input, but also guarantees the robustness of the multi-area power network, which has an effect on parametric uncertainties such as the load variations and the matched or mismatched parameter uncertainties. Moreover, the reporting of the simulation indicates that the proposed controller upholds the quality requirement by controlling with operating conditions in the larger range, rejects disturbance, reduces the transient response of frequency, eliminates the overshoot problem, and can better address load uncertainties compared to several previous control methods. The simulation results also show that the proposed SOISMC can be used for practical multi-area power network to lessen high parameter uncertainties and load disturbances.

ACS Style

Van Van Huynh; Phong Thanh Tran; Bui Le Ngoc Minh; Anh-Tuan Tran; Dao Huy Tuan; Tam Minh Nguyen; Phan-Tu Vu. New Second-Order Sliding Mode Control Design for Load Frequency Control of a Power System. Energies 2020, 13, 6509 .

AMA Style

Van Van Huynh, Phong Thanh Tran, Bui Le Ngoc Minh, Anh-Tuan Tran, Dao Huy Tuan, Tam Minh Nguyen, Phan-Tu Vu. New Second-Order Sliding Mode Control Design for Load Frequency Control of a Power System. Energies. 2020; 13 (24):6509.

Chicago/Turabian Style

Van Van Huynh; Phong Thanh Tran; Bui Le Ngoc Minh; Anh-Tuan Tran; Dao Huy Tuan; Tam Minh Nguyen; Phan-Tu Vu. 2020. "New Second-Order Sliding Mode Control Design for Load Frequency Control of a Power System." Energies 13, no. 24: 6509.

Journal article
Published: 02 July 2020 in Energies
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The continuous development of fifth generation (5G) communication and Internet of Thing (IoT) inevitably necessitates more advanced systems that can satisfy the growing wireless data rate demand of future equipment. Device-to-Device (D2D) communication, whose performance is evaluated in terms of the overall throughput, energy efficiency (EE) and spectral efficiency (SE), is considered a promising solution for the aforementioned problem. Thereby, this paper aims at improving the performance of the D2D communication underlaying cellular networks operating on multiple bands by maximizing the EE in its uplink. Thanks to the stochastic geometry theory, it is possible to derive the closed-form expressions for the successful transmission probability (STP), the total average transmission rate (TATR), and the total average energy efficiency (TAEE) of cellular and D2D users in different time slot setting. Particularly investigated and compared in this study, there are one-hop, direct, D2D communication in two time slots (2TS), and multi-hop, indirect, D2D communication in three time slots (3TS) with an additional D2D user acting as a two-way relay to assist the communication. Moreover, an optimization problem is formulated to calculate the maximum TAEE of D2D users and the optimum transmission power of both the cellular and D2D users. Herein this optimization study, which is proven to be non-convex, the Quality of Service (QoS) is ensured as the STP on every link is considered. The herein approach is referred to as relay-assisted D2D communication which is capable of delivering a notably better QoS and lower transmission power for communication among distant D2D users.

ACS Style

Van-Van Huynh; Nguyen Tan-Loc; Ma Quoc-Phu; Lukas Sevcik; Hoang-Sy Nguyen; Miroslav Voznak. Energy Efficiency Maximization of Two-Time-Slot and Three-Time-Slot Two-Way Relay-Assisted Device-to-Device Underlaying Cellular Networks. Energies 2020, 13, 3422 .

AMA Style

Van-Van Huynh, Nguyen Tan-Loc, Ma Quoc-Phu, Lukas Sevcik, Hoang-Sy Nguyen, Miroslav Voznak. Energy Efficiency Maximization of Two-Time-Slot and Three-Time-Slot Two-Way Relay-Assisted Device-to-Device Underlaying Cellular Networks. Energies. 2020; 13 (13):3422.

Chicago/Turabian Style

Van-Van Huynh; Nguyen Tan-Loc; Ma Quoc-Phu; Lukas Sevcik; Hoang-Sy Nguyen; Miroslav Voznak. 2020. "Energy Efficiency Maximization of Two-Time-Slot and Three-Time-Slot Two-Way Relay-Assisted Device-to-Device Underlaying Cellular Networks." Energies 13, no. 13: 3422.

Journal article
Published: 27 May 2020 in Symmetry
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Recently, hidden attractors with stable equilibria have received considerable attention in chaos theory and nonlinear dynamical systems. Based on discrete fractional calculus, this paper proposes a simple two-dimensional and three-dimensional fractional maps. Both fractional maps are chaotic and have a unique equilibrium point. Results show that the dynamics of the proposed fractional maps are sensitive to both initial conditions and fractional order. There are coexisting attractors which have been displayed in terms of bifurcation diagrams, phase portraits and a 0-1 test. Furthermore, control schemes are introduced to stabilize the chaotic trajectories of the two novel systems.

ACS Style

Adel Ouannas; Othman Abdullah Almatroud; Amina Aicha Khennaoui; Mohammad Mossa Al-Sawalha; Dumitru Baleanu; Van Van Huynh; Viet-Thanh Pham. Bifurcations, Hidden Chaos and Control in Fractional Maps. Symmetry 2020, 12, 879 .

AMA Style

Adel Ouannas, Othman Abdullah Almatroud, Amina Aicha Khennaoui, Mohammad Mossa Al-Sawalha, Dumitru Baleanu, Van Van Huynh, Viet-Thanh Pham. Bifurcations, Hidden Chaos and Control in Fractional Maps. Symmetry. 2020; 12 (6):879.

Chicago/Turabian Style

Adel Ouannas; Othman Abdullah Almatroud; Amina Aicha Khennaoui; Mohammad Mossa Al-Sawalha; Dumitru Baleanu; Van Van Huynh; Viet-Thanh Pham. 2020. "Bifurcations, Hidden Chaos and Control in Fractional Maps." Symmetry 12, no. 6: 879.

Journal article
Published: 25 May 2020 in Symmetry
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Chaotic systems have attracted considerable attention and been applied in various applications. Investigating simple systems and counterexamples with chaotic behaviors is still an important topic. The purpose of this work was to study a simple symmetrical system including only five nonlinear terms. We discovered the system’s rich behavior such as chaos through phase portraits, bifurcation diagrams, Lyapunov exponents, and entropy. Interestingly, multi-stability was observed when changing system’s initial conditions. Chaos of such a system was predicted by applying a machine learning approach based on a neural network.

ACS Style

Vo Phu Thoai; Maryam Shahriari Kahkeshi; Van Van Huynh; Adel Ouannas; Viet-Thanh Pham. A Nonlinear Five-Term System: Symmetry, Chaos, and Prediction. Symmetry 2020, 12, 865 .

AMA Style

Vo Phu Thoai, Maryam Shahriari Kahkeshi, Van Van Huynh, Adel Ouannas, Viet-Thanh Pham. A Nonlinear Five-Term System: Symmetry, Chaos, and Prediction. Symmetry. 2020; 12 (5):865.

Chicago/Turabian Style

Vo Phu Thoai; Maryam Shahriari Kahkeshi; Van Van Huynh; Adel Ouannas; Viet-Thanh Pham. 2020. "A Nonlinear Five-Term System: Symmetry, Chaos, and Prediction." Symmetry 12, no. 5: 865.

Journal article
Published: 12 March 2020 in Sustainability
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The aim of this study was twofold: (1) to assess the performance accuracy of support vector machine (SVM) models with different kernels to predict rock brittleness and (2) compare the inputs’ importance in different SVM models. To this end, the authors developed eight SVM models with different kernel types, i.e., the radial basis function (RBF), the linear (LIN), the sigmoid (SIG), and the polynomial (POL). Four of these models were developed using only the SVM method, while the four other models were hybridized with a feature selection (FS) technique. The performance of each model was assessed using five performance indices and a simple ranking system. The results of this study show that the SVM models developed using the RBF kernel achieved the highest ranking values among single and hybrid models. Concerning the importance of variables for predicting the brittleness index (BI), the Schmidt hammer rebound number (Rn) was identified as the most important variable by the three single-based models, developed by POL, SIG, and LIN kernels. However, the single SVM model developed by RBF identified density as the most important input variable. Concerning the hybrid SVM models, three models that were developed using the RBF, POL, and SIG kernels identified the point load strength index as the most important input, while the model developed using the LIN identified the Rn as the most important input. All four single-based SVM models identified the p-wave velocity (Vp) as the least important input. Concerning the least important factors for predicting the BI of the rock in hybrid-based models, Vp was identified as the least important factor by FS-SVM-POL, FS-SVM-SIG, and FS-SVM-LIN, while the FS-SVM-RBF identified Rn as the least important input.

ACS Style

Danial Jahed Armaghani; Panagiotis G. Asteris; Behnam Askarian; Mahdi Hasanipanah; Reza Tarinejad; Van Van Huynh. Examining Hybrid and Single SVM Models with Different Kernels to Predict Rock Brittleness. Sustainability 2020, 12, 2229 .

AMA Style

Danial Jahed Armaghani, Panagiotis G. Asteris, Behnam Askarian, Mahdi Hasanipanah, Reza Tarinejad, Van Van Huynh. Examining Hybrid and Single SVM Models with Different Kernels to Predict Rock Brittleness. Sustainability. 2020; 12 (6):2229.

Chicago/Turabian Style

Danial Jahed Armaghani; Panagiotis G. Asteris; Behnam Askarian; Mahdi Hasanipanah; Reza Tarinejad; Van Van Huynh. 2020. "Examining Hybrid and Single SVM Models with Different Kernels to Predict Rock Brittleness." Sustainability 12, no. 6: 2229.

Journal article
Published: 11 March 2020 in Applied Sciences
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In civil engineering applications, piles (deep foundations) are pushed into the ground in order to perform as steady support of structures. As these type of foundations are able to carry a huge amount of load, they should be carefully designed in terms of their settlement. Therefore, the control and estimation of settlement is a significant issue in pilling design and construction. The objective of the present study is to introduce a modeling process of a hybrid intelligence system namely neural network optimized by particle swarm optimization (neuro-swarm) for estimation of pile settlement. To do that, properties results of several piles socketed into rock mass together with their settlements were considered as established databased to propose neuro-swarm model. Then, several sensitivity analyses were carried out to determine the most influential particle swarm optimization parameters for pile settlement prediction. Eventually, five neuro-swarm models were constructed to understand the behavior of this hybrid model on them in pile settlement prediction. As a result, according to results of five performance indices, dataset number 4 showed the highest prediction capacity among all five datasets. The coefficient of determination (R2) and system error values of (0.851 and 0.079) and (0.892 and 0.099) were obtained respectively for train and test stages of the best neuro-swarm model which reveal the capability level of this hybrid model in predicting pile settlement. The modeling process introduced in this study can be useful for the researchers who are interested to work on the same hybrid technique.

ACS Style

Danial Jahed Armaghani; Panagiotis G. Asteris; Seyed Alireza Fatemi; Mahdi Hasanipanah; Reza Tarinejad; Ahmad Safuan A. Rashid; Van Van Huynh. On the Use of Neuro-Swarm System to Forecast the Pile Settlement. Applied Sciences 2020, 10, 1904 .

AMA Style

Danial Jahed Armaghani, Panagiotis G. Asteris, Seyed Alireza Fatemi, Mahdi Hasanipanah, Reza Tarinejad, Ahmad Safuan A. Rashid, Van Van Huynh. On the Use of Neuro-Swarm System to Forecast the Pile Settlement. Applied Sciences. 2020; 10 (6):1904.

Chicago/Turabian Style

Danial Jahed Armaghani; Panagiotis G. Asteris; Seyed Alireza Fatemi; Mahdi Hasanipanah; Reza Tarinejad; Ahmad Safuan A. Rashid; Van Van Huynh. 2020. "On the Use of Neuro-Swarm System to Forecast the Pile Settlement." Applied Sciences 10, no. 6: 1904.

Journal article
Published: 04 March 2020 in Applied Sciences
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Seepage is one of the most challenging issues in some procedures such as design, construction, and operation of embankment or earth fill dams. The purpose of this research is to develop a new solution based on governing equations to solve the seepage problem in an effective way. Therefore, by implementing the equations in the programming environment, more than 24,000 models were designed to be applicable to different conditions. Input data included different parameters such as slopes in upstream and downstream, embankment width, soil permeability coefficient, height, and freeboard. With the use of this big data, a new process was developed to provide simple mathematical models for the seepage rate analysis. The study first used intelligent models to simulate the seepage behavior. Finally, the accuracy of the models was optimized using a new metaheuristic algorithm. This led to the ultimate flexibility of the final model presented as a new solution capable of evaluating different conditions. Finally, using the best model, new mathematical relationships were developed based on this methodology. This new solution can be used as a proper alternative to the governing equations of seepage rate estimation. Another advantage of the proposed model is its high flexibility that can be well applied to engineering design in this field, which was not possible using the initial equations.

ACS Style

Dongchun Tang; Behrouz Gordan; Mohammadreza Koopialipoor; Danial Jahed Armaghani; Reza Tarinejad; Binh Thai Pham; Van Van Huynh. Seepage Analysis in Short Embankments Using Developing a Metaheuristic Method Based on Governing Equations. Applied Sciences 2020, 10, 1761 .

AMA Style

Dongchun Tang, Behrouz Gordan, Mohammadreza Koopialipoor, Danial Jahed Armaghani, Reza Tarinejad, Binh Thai Pham, Van Van Huynh. Seepage Analysis in Short Embankments Using Developing a Metaheuristic Method Based on Governing Equations. Applied Sciences. 2020; 10 (5):1761.

Chicago/Turabian Style

Dongchun Tang; Behrouz Gordan; Mohammadreza Koopialipoor; Danial Jahed Armaghani; Reza Tarinejad; Binh Thai Pham; Van Van Huynh. 2020. "Seepage Analysis in Short Embankments Using Developing a Metaheuristic Method Based on Governing Equations." Applied Sciences 10, no. 5: 1761.

Journal article
Published: 02 March 2020 in Applied Sciences
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Despite the vast usage of machine learning techniques to solve engineering problems, a very limited number of studies on the rock brittleness index (BI) have used these techniques to analyze issues in this field. The present study developed five well-known machine learning techniques and compared their performance to predict the brittleness index of the rock samples. The comparison of the models’ performance was conducted through a ranking system. These techniques included Chi-square automatic interaction detector (CHAID), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), and artificial neural network (ANN). This study used a dataset from a water transfer tunneling project in Malaysia. Results of simple rock index tests i.e., Schmidt hammer, p-wave velocity, point load, and density were considered as model inputs. The results of this study indicated that while the RF model had the best performance for training (ranking = 25), the ANN outperformed other models for testing (ranking = 22). However, the KNN model achieved the highest cumulative ranking, which was 37. The KNN model showed desirable stability for both training and testing. However, the results of validation stage indicated that RF model with coefficient of determination (R2) of 0.971 provides higher performance capacity for prediction of the rock BI compared to KNN model with R2 of 0.807 and ANN model with R2 of 0.860. The results of this study suggest a practical use of the machine learning models in solving problems related to rock mechanics specially rock brittleness index.

ACS Style

Deliang Sun; Mahshid Lonbani; Behnam Askarian; Danial Jahed Armaghani; Reza Tarinejad; Binh Thai Pham; Van Van Huynh. Investigating the Applications of Machine Learning Techniques to Predict the Rock Brittleness Index. Applied Sciences 2020, 10, 1691 .

AMA Style

Deliang Sun, Mahshid Lonbani, Behnam Askarian, Danial Jahed Armaghani, Reza Tarinejad, Binh Thai Pham, Van Van Huynh. Investigating the Applications of Machine Learning Techniques to Predict the Rock Brittleness Index. Applied Sciences. 2020; 10 (5):1691.

Chicago/Turabian Style

Deliang Sun; Mahshid Lonbani; Behnam Askarian; Danial Jahed Armaghani; Reza Tarinejad; Binh Thai Pham; Van Van Huynh. 2020. "Investigating the Applications of Machine Learning Techniques to Predict the Rock Brittleness Index." Applied Sciences 10, no. 5: 1691.

Journal article
Published: 27 January 2020 in Applied Sciences
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In mining and civil engineering applications, a reliable and proper analysis of ground vibration due to quarry blasting is an extremely important task. While advances in machine learning led to numerous powerful regression models, the usefulness of these models for modeling the peak particle velocity (PPV) remains largely unexplored. Using an extensive database comprising quarry site datasets enriched with vibration variables, this article compares the predictive performance of five selected machine learning classifiers, including classification and regression trees (CART), chi-squared automatic interaction detection (CHAID), random forest (RF), artificial neural network (ANN), and support vector machine (SVM) for PPV analysis. Before conducting these model developments, feature selection was applied in order to select the most important input parameters for PPV. The results of this study show that RF performed substantially better than any of the other investigated regression models, including the frequently used SVM and ANN models. The results and process analysis of this study can be utilized by other researchers/designers in similar fields.

ACS Style

Hong Zhang; Jian Zhou; Danial Jahed Armaghani; M. M. Tahir; Binh Thai Pham; Van Van Huynh. A Combination of Feature Selection and Random Forest Techniques to Solve a Problem Related to Blast-Induced Ground Vibration. Applied Sciences 2020, 10, 869 .

AMA Style

Hong Zhang, Jian Zhou, Danial Jahed Armaghani, M. M. Tahir, Binh Thai Pham, Van Van Huynh. A Combination of Feature Selection and Random Forest Techniques to Solve a Problem Related to Blast-Induced Ground Vibration. Applied Sciences. 2020; 10 (3):869.

Chicago/Turabian Style

Hong Zhang; Jian Zhou; Danial Jahed Armaghani; M. M. Tahir; Binh Thai Pham; Van Van Huynh. 2020. "A Combination of Feature Selection and Random Forest Techniques to Solve a Problem Related to Blast-Induced Ground Vibration." Applied Sciences 10, no. 3: 869.

Original article
Published: 09 January 2020 in Engineering with Computers
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The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP) tree-based, and simulated annealing–GP or SA–GP for prediction of the ultimate-bearing capacity (Qult) of the pile. The collected database consists of 50 driven piles properties with pile length, pile cross-sectional area, hammer weight, pile set and drop height as model inputs and Qult as model output. Many GP and SA–GP models were constructed for estimating pile bearing capacity and the best models were selected using some performance indices. For comparison purposes, the ANFIS model was also applied to predict Qult of the pile. It was observed that the developed models are able to provide higher prediction performance in the design of Qult of the pile. Concerning the coefficient of correlation, and mean square error, the SA–GP model had the best values for both training and testing data sets, followed by the GP and ANFIS models, respectively. It implies that the neural-based predictive machine learning techniques like ANFIS are not as powerful as evolutionary predictive machine learning techniques like GP and SA–GP in estimating the ultimate-bearing capacity of the pile. Besides, GP and SA–GP can propose a formula for Qult prediction which is a privilege of these models over the ANFIS predictive model. The sensitivity analysis also showed that the Qult of pile looks to be more affected by pile cross-sectional area and pile set.

ACS Style

Weixun Yong; Jian Zhou; Danial Jahed Armaghani; M. M. Tahir; Reza Tarinejad; Binh Thai Pham; Van Van Huynh. A new hybrid simulated annealing-based genetic programming technique to predict the ultimate bearing capacity of piles. Engineering with Computers 2020, 1 -17.

AMA Style

Weixun Yong, Jian Zhou, Danial Jahed Armaghani, M. M. Tahir, Reza Tarinejad, Binh Thai Pham, Van Van Huynh. A new hybrid simulated annealing-based genetic programming technique to predict the ultimate bearing capacity of piles. Engineering with Computers. 2020; ():1-17.

Chicago/Turabian Style

Weixun Yong; Jian Zhou; Danial Jahed Armaghani; M. M. Tahir; Reza Tarinejad; Binh Thai Pham; Van Van Huynh. 2020. "A new hybrid simulated annealing-based genetic programming technique to predict the ultimate bearing capacity of piles." Engineering with Computers , no. : 1-17.

Journal article
Published: 22 April 2019 in Computer Networks
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This paper looks into an energy harvesting (EH) relay-enabled cognitive radio wireless sensor network (CR-WSN) considering power splitting (PS) architecture. More specifically, a relay (RU) harvesting energy from the signals transmitted from a secondary user transmitter (ST,) and using the harvested energy to forward the resulting signals to another sensor node subsequently is being investigated. This scheme can be broken down into two components, i.e., a sensor node physically placed near the transmitter (SPNT) and a sensor node physically placed far from the transmitter (SPFT). The closed-form expressions for the successful transmission probability (STP) and the achievable data rate in both cases can be derived analytically. In order to quantify the energy consumption, the system energy efficiency (EE) is examined. Furthermore, the achievable data rate was optimized in three possible scenarios, i.e., the trade-off between the sum data rate and the sum harvested energy (R-E), the achievable data rate at RU, and the joint optimization of the power allocation and PS ratio in case of SPNT. A Monte Carlo simulation has been performed to verify the theoretical analysis obtained, and to show the impact of different parameters on system performance.

ACS Style

Van-Van Huynh; Hoang-Sy Nguyen; Ly Tran Thai Hoc; Thanh-Sang Nguyen; Miroslav Voznak. Optimization issues for data rate in energy harvesting relay-enabled cognitive sensor networks. Computer Networks 2019, 157, 29 -40.

AMA Style

Van-Van Huynh, Hoang-Sy Nguyen, Ly Tran Thai Hoc, Thanh-Sang Nguyen, Miroslav Voznak. Optimization issues for data rate in energy harvesting relay-enabled cognitive sensor networks. Computer Networks. 2019; 157 ():29-40.

Chicago/Turabian Style

Van-Van Huynh; Hoang-Sy Nguyen; Ly Tran Thai Hoc; Thanh-Sang Nguyen; Miroslav Voznak. 2019. "Optimization issues for data rate in energy harvesting relay-enabled cognitive sensor networks." Computer Networks 157, no. : 29-40.

Conference paper
Published: 13 April 2019 in Lecture Notes in Electrical Engineering
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This paper presents a new analysis method to design an observer- based control for a class of mismatched uncertain time-delay system with mismatched uncertainties in the output matrix. One of the contributions is to estimate the current true value of the system state variables, avoiding the effect of the delayed and noised measurement output. Linear matrix inequality (LMI) approach is used to design the observer-based control. The control and observer gains matrices are characterized using the solution of the LMI existence condition.

ACS Style

Van Van Huynh; Tran Thanh Phong; Bach Hoang Dinh. Observer Based Control for Systems with Mismatched Uncertainties in Output Matrix. Lecture Notes in Electrical Engineering 2019, 561 -568.

AMA Style

Van Van Huynh, Tran Thanh Phong, Bach Hoang Dinh. Observer Based Control for Systems with Mismatched Uncertainties in Output Matrix. Lecture Notes in Electrical Engineering. 2019; ():561-568.

Chicago/Turabian Style

Van Van Huynh; Tran Thanh Phong; Bach Hoang Dinh. 2019. "Observer Based Control for Systems with Mismatched Uncertainties in Output Matrix." Lecture Notes in Electrical Engineering , no. : 561-568.

Journal article
Published: 14 March 2019 in Entropy
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A map without equilibrium has been proposed and studied in this paper. The proposed map has no fixed point and exhibits chaos. We have investigated its dynamics and shown its chaotic behavior using tools such as return map, bifurcation diagram and Lyapunov exponents’ diagram. Entropy of this new map has been calculated. Using an open micro-controller platform, the map is implemented, and experimental observation is presented. In addition, two control schemes have been proposed to stabilize and synchronize the chaotic map.

ACS Style

Van Van Huynh; Adel Ouannas; Xiong Wang; Viet-Thanh Pham; Xuan Quynh Nguyen; Fawaz E. Alsaadi. Chaotic Map with No Fixed Points: Entropy, Implementation and Control. Entropy 2019, 21, 279 .

AMA Style

Van Van Huynh, Adel Ouannas, Xiong Wang, Viet-Thanh Pham, Xuan Quynh Nguyen, Fawaz E. Alsaadi. Chaotic Map with No Fixed Points: Entropy, Implementation and Control. Entropy. 2019; 21 (3):279.

Chicago/Turabian Style

Van Van Huynh; Adel Ouannas; Xiong Wang; Viet-Thanh Pham; Xuan Quynh Nguyen; Fawaz E. Alsaadi. 2019. "Chaotic Map with No Fixed Points: Entropy, Implementation and Control." Entropy 21, no. 3: 279.

Journal article
Published: 10 February 2019 in Electronics
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This paper discusses the real-time optimal path planning of autonomous humanoid robots in unknown environments regarding the absence and presence of the danger space. The danger is defined as an environment which is not an obstacle nor free space and robot are permitted to cross when no free space options are available. In other words, the danger can be defined as the potentially risky areas of the map. For example, mud pits in a wooded area and greasy floor in a factory can be considered as a danger. The synthetic potential field, linguistic method, and Markov decision processes are methods which have been reviewed for path planning in a free-danger unknown environment. The modified Markov decision processes based on the Takagi–Sugeno fuzzy inference system is implemented to reach the target in the presence and absence of the danger space. In the proposed method, the reward function has been calculated without the exact estimation of the distance and shape of the obstacles. Unlike other existing path planning algorithms, the proposed methods can work with noisy data. Additionally, the entire motion planning procedure is fully autonomous. This feature makes the robot able to work in a real situation. The discussed methods ensure the collision avoidance and convergence to the target in an optimal and safe path. An Aldebaran humanoid robot, NAO H25, has been selected to verify the presented methods. The proposed methods require only vision data which can be obtained by only one camera. The experimental results demonstrate the efficiency of the proposed methods.

ACS Style

Hadi Jahanshahi; Mohsen Jafarzadeh; Naeimeh Najafizadeh Sari; Viet-Thanh Pham; Van Van Huynh; Xuan Quynh Nguyen. Robot Motion Planning in an Unknown Environment with Danger Space. Electronics 2019, 8, 201 .

AMA Style

Hadi Jahanshahi, Mohsen Jafarzadeh, Naeimeh Najafizadeh Sari, Viet-Thanh Pham, Van Van Huynh, Xuan Quynh Nguyen. Robot Motion Planning in an Unknown Environment with Danger Space. Electronics. 2019; 8 (2):201.

Chicago/Turabian Style

Hadi Jahanshahi; Mohsen Jafarzadeh; Naeimeh Najafizadeh Sari; Viet-Thanh Pham; Van Van Huynh; Xuan Quynh Nguyen. 2019. "Robot Motion Planning in an Unknown Environment with Danger Space." Electronics 8, no. 2: 201.

Journal article
Published: 01 February 2019 in Sensors
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Thanks to the benefits of non-orthogonal multiple access (NOMA) in wireless communications, we evaluate a wireless sensor network deploying NOMA (WSN-NOMA), where the destination can receive two data symbols in a whole transmission process with two time slots. In this work, two relaying protocols, so-called time-switching-based relaying WSN-NOMA (TSR WSN-NOMA) and power-splitting-based relaying WSN-NOMA (PSR WSN-NOMA) are deployed to study energy-harvesting (EH). Regarding the system performance analysis, we obtain the closed-form expressions for the exact and approximate outage probability (OP) in both protocols, and the delay-limited throughput is also evaluated. We then compare the two protocols theoretically, and two optimization problems are formulated to reduce the impact of OP and optimize the data rate. Our numerical and simulation results are provided to prove the theoretical and analytical analysis. Thanks to these results, a great performance gain can be achieved for both TSR WSN-NOMA and PSR WSN-NOMA if optimal values of TS and PS ratios are found. In addition, the optimized TSR WSN-NOMA outperforms that of PSR WSN-NOMA in terms of OP.

ACS Style

Hoang-Sy Nguyen; Tran Thai Hoc Ly; Thanh-Sang Nguyen; Van Van Huynh; Miroslav Voznak. Outage Performance Analysis and SWIPT Optimization in Energy-Harvesting Wireless Sensor Network Deploying NOMA. Sensors 2019, 19, 613 .

AMA Style

Hoang-Sy Nguyen, Tran Thai Hoc Ly, Thanh-Sang Nguyen, Van Van Huynh, Miroslav Voznak. Outage Performance Analysis and SWIPT Optimization in Energy-Harvesting Wireless Sensor Network Deploying NOMA. Sensors. 2019; 19 (3):613.

Chicago/Turabian Style

Hoang-Sy Nguyen; Tran Thai Hoc Ly; Thanh-Sang Nguyen; Van Van Huynh; Miroslav Voznak. 2019. "Outage Performance Analysis and SWIPT Optimization in Energy-Harvesting Wireless Sensor Network Deploying NOMA." Sensors 19, no. 3: 613.

Journal article
Published: 10 January 2019 in Symmetry
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In recent years, non-orthogonal multiple access (NOMA) has become a promising technology for the advancement of future wireless communications. In principle, the relay node with better channel conditions can support others to enhance the system performance by using successive interference cancellation (SIC) technique. In this paper, we take advantage of NOMA in the study of a relaying cooperative system operating in half-duplex (HD) fixed decode-and-forward (DF) relaying scheme. In the two time slots, two data symbols are received at the destination node resulting in a higher transmission rate. Besides that, we study energy harvesting (EH) with power splitting (PS) protocol. For performance analysis, approximate and exact closed-form expressions for outage probability (OP) are obtained. Following that, we examine the average bit error probability (ABEP) while expressions for the throughput in delay-limited mode are given. It can be seen that our simulation results match well with the Monte Carlo simulations.

ACS Style

Tran Thai Hoc Ly; Hoang-Sy Nguyen; Thanh-Sang Nguyen; Van Van Huynh; Miroslav Voznak; Thanh-Long Nguyen. Outage Probability Analysis in Relaying Cooperative Systems with NOMA Considering Power Splitting. Symmetry 2019, 11, 72 .

AMA Style

Tran Thai Hoc Ly, Hoang-Sy Nguyen, Thanh-Sang Nguyen, Van Van Huynh, Miroslav Voznak, Thanh-Long Nguyen. Outage Probability Analysis in Relaying Cooperative Systems with NOMA Considering Power Splitting. Symmetry. 2019; 11 (1):72.

Chicago/Turabian Style

Tran Thai Hoc Ly; Hoang-Sy Nguyen; Thanh-Sang Nguyen; Van Van Huynh; Miroslav Voznak; Thanh-Long Nguyen. 2019. "Outage Probability Analysis in Relaying Cooperative Systems with NOMA Considering Power Splitting." Symmetry 11, no. 1: 72.