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Fractional-order sliding mode controller for the two-link robot arm Trong-Thang Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp5579-5585

Abstract

In this paper, the author proposes a sliding mode controller with the fractional-order for the two-link robot arm. Firstly, the model and dynamic equations of the two-link robot arm are presented. Based on these equations, the author builds the controller for each joint of the robot. The controller is a sliding mode controller with its order is not an integer value. The task of the controller is to adjust the torques acted on the joints in order for the angular coordinates of each link to coincide with the desired values. The effectiveness of the proposed control system is demonstrated through Matlab-Simulink software. The robot model and controller are built to investigate the system quality. The results show that the quality of the control system is very high: there is not the chattering phenomenon of torques, the response angles of each link quickly reach the desired values, and the static error equal to zero.
The neural network-based control system of direct current motor driver Trong-Thang Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.824 KB) | DOI: 10.11591/ijece.v9i2.pp1445-1452

Abstract

This article aims to propose an adaptive control system for the direct current motor driver based on the neural network. The control system consists of two neural networks: the first neural network is used to estimate the speed of the direct current motor and the second neural network is used as a controller. The plant in this research includes motor and the driver circuit so it is a complex model. It is difficult to determine the exact parameters of the plant so it is difficult to build the controller. To solve the above difficulties, the author proposes an adaptive control system based on the neural network to control the plant reach the high quality in the case of unknowing the parameters of the plant. The results are that the control quality of the system is very good, the response speed always follows the desired speed and the transition time is small. The simulation results of the neural network control system are shown and compared with that of a PID controller to demonstrate the advantages of the proposed method.
The maximum power point tracking based-control system for small-scale wind turbine using fuzzy logic Quang-Vi Ngo; Chai Yi; Trong-Thang Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1106.328 KB) | DOI: 10.11591/ijece.v10i4.pp3927-3935

Abstract

This paper presents the research on small-scale wind turbine systems based on the Maximum Power Point Tracking (MPPT) algorithm. Then propose a new structure of a small-scale wind turbine system to simplify the structure of the system, making the system highly practical. This paper also presented an MPPT-Fuzzy controller design and proposed a control system using the wind speed sensor for small-scale wind turbines. Systems are simulated using Matlab/Simulink software to evaluate the feasibility of the proposed controller. As a result, the system with the MPPT-Fuzzy controller has much better quality than the traditional control system.
Sliding mode control-based system for the two-link robot arm Trong-Thang Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (34.481 KB) | DOI: 10.11591/ijece.v9i4.pp2771-2778

Abstract

In this research, the author presents the model of the two-link robot arm and its dynamic equations. Based on these dynamic equations, the author builds the sliding mode controller for each joint of the robot. The tasks of the controllers are controlling the Torque in each Joint of the robot in order that the angle coordinates of each link coincide with the desired values. The proposed algorithm and robot model are built on Matlab-Simulink to investigate the system quality. The results show that the quality of the control system is very high: the response angles of each link quickly reach the desired values, and the static error equal to zero.
The MPPT algorithm combined with pitch angle control for the small-scale wind turbine in a wide speed range Quang-Vi Ngo; Trong-Thang Nguyen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 12, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v12.i3.pp1482-1493

Abstract

This research proposes the control system structure for a small-scale wind turbine. Significantly, the maximum power point tracking algorithm (MPPT) and the pitch angle controller are deeply analyzed; this is the base for proposing the strategy of the MPPT algorithm combined with pitch-angle control in a wide speed range of wind. This article also researches the converters, then analyses the advantages of each converter to choose the suitable converter for the small-scale wind turbine. In the MPPT algorithm design, the expert experience takes advantage through the fuzzy controller. The pitch angle controller is built based on the PID controller with its parameters adjusted by Fuzzy logic. The results showed that the effectiveness of the proposed control strategy is much better than that of the traditional control strategy. Moreover, in high and low wind speeds, the proposed control system operates reliably and stably.
The fuzzy-PID based-pitch angle controller for small-scale wind turbine Quang-Vi Ngo; Chai Yi; Trong-Thang Nguyen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (14875.218 KB) | DOI: 10.11591/ijpeds.v11.i1.pp135-142

Abstract

This paper aims to design the pitch angle control based on proportional–integral–derivative (PID) controller combined with fuzzy logic for small-scale wind turbine systems. In this control system, the pitch angle is controlled by the PID controller with their parameter is tuned by the fuzzy logic controller. This control system can compensate for the nonlinear characteristic of the pitch angle and wind speed. A comparison between the fuzzy-PID-controller with the conventional PID controller is carried out. The effectiveness of the method is determined by the simulation results of a small wind turbine using a permanent magnet generator (PMSG).
The linear quadratic regular algorithm-based control system of the direct current motor Trong-Thang Nguyen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.168 KB) | DOI: 10.11591/ijpeds.v10.i2.pp768-776

Abstract

This research aims to propose an optimal controller for controlling the speed of the Direct Current (DC) motor. Based on the mathematical equations of DC Motor, the author builds the equations of the state space model and builds the linear quadratic regulator (LQR) controller to minimize the error between the set speed and the response speed of DC motor. The results of the proposed controller are compared with the traditional controllers as the PID, the feed-forward controller. The simulation results show that the quality of the control system in the case of LQR controller is much higher than the traditional controllers. The response speed always follows the set speed with the short conversion time, there isn't overshoot. The response speed is almost unaffected when the torque impact on the shaft is changed.
A Suitable Structure to Control the System of Quad-rotor Miniature Aerial Vehicles Van-Dai Bui; Trong-Thang Nguyen; Ngoc-Hoan Than; Duc-Minh Nguyen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1303.158 KB) | DOI: 10.11591/ijpeds.v9.i4.pp1634-1643

Abstract

Miniature Aerial Vehicles with four rotors is called Quad-rotor MAV, popularly used in aspects of life such military, civilian products, processes and remote sensor, etc. In this paper, the authors present the suitable structure of control system for the Quad-rotor MAV. The first, the Six Degrees of Freedom (6 DOF) of the Quad-rotor MAV dynamic model is built. After, the control structure with the single loop is built. But in the single-loop system, only four control signals of Quad-rotor MAV can be controlled, so the Quad-rotor MAV can be reached the height only and keep the stability. However, it is important to note that we have to well-known the orbit of the Quad-rotor MAV flight; the Quad-rotor MAV must fly point-to-point exactly, so the six coordinate variables must be controlled. So, the double loop control structure system is proposed to do that. Finally, the simulation results analysis and the experimental results of the real model are explored to prove the effectiveness of the proposed structure.
A neural network combined with sliding mode controller for the two-wheel self-balancing robot Duc-Minh Nguyen; Van-Tiem Nguyen; Trong-Thang Nguyen
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i3.pp592-601

Abstract

This article presents the sliding control method combined with the selfadjusting neural network to compensate for noise to improve the control system's quality for the two-wheel self-balancing robot. Firstly, the dynamic equations of the two-wheel self-balancing robot built by Euler–Lagrange is the basis for offering control laws with a neural network of noise compensation. After disturbance-compensating, the sliding mode controller is applied to control quickly the two-wheel self-balancing robot reached the desired position. The stability of the proposed system is proved based on the Lyapunov theory. Finally, the simulation results will confirm the effectiveness and correctness of the control method suggested by the authors.
The MRAC based-adaptive control system for controlling the speed of direct current motor Manh-Cuong Nguyen; Duc-Phuc Vuong; Trong-Thang Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp723-728

Abstract

This research aims to propose an adaptive control system for controlling the speed of the direct current (DC) motor. The system consists of two control loops: the first control loop is a traditional PID controller and the second control loop is an adaptive controller. The role of the adaptive controller is adjusting the output of the control object follows with the output of the reference model. The adjustment mechanism is very simple, but the quality of the whole system is very high: the conversion time is short and there isn't overshoot. The quality of the proposed adaptive control system is also compared to the traditional PID control system to show the advantages of the new system.