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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Journal of Engineering and Technological Sciences
Nguyen Hong Quang
Thai Nguyen University of Technology
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Impact analysis of actuator torque degradation on the IRB 120 robot performance using simscape-based model Le Ngoc Truc; Nguyen Phung Quang; Nguyen Hong Quang
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4850-4864

Abstract

Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
On tracking control problem for polysolenoid motor model predictive approach Nguyen Hong Quang; Nguyen Phung Quang; Do Trung Hai; Nguyen Nhu Hien
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (513.65 KB) | DOI: 10.11591/ijece.v10i1.pp849-855

Abstract

The Polysolenoid Linear Motor (PLM) have been playing a crucial role in many industrial aspects due to its functions, in which a straight motion is provided directly without mediate mechanical actuators. Recently, with several commons on mathematic model, some control methods for PLM based on Rotational Motor have been applied, but position, velocity and current constraints which are important in real systems have been ignored. In this paper, position tracking control problem for PLM was considered under state-independent disturbances via min-max model predictive control. The proposed controller forces tracking position errors converge to small region of origin and satisfies state including position, velocity and currents constraints. Further, a numerical simulation was implemented to validate the performance of the proposed controller.
A sensorless approach for tracking control problem of tubular linear synchronous motor Nguyen Hong Quang; Nguyen Phung Quang; Nguyen Van Lanh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2393-2404

Abstract

As well-known, linear motors are widely applied to various industrial applicationsdue to their abilities in providing directly straight movement without auxiliary mechanical transmissions. This paper addresses the sensorless control problem of tubular linear synchronous motors, which belong to a family of permanent magnet linear motor. To be specific, a novel velocity observer is proposed to deal with an unmeasurable velocity problem, and asymptotic convergence of the observer error is ensured. Unlike other studies on sensorless control methods for linear motors, our proposed observer is designed by regrading unknown disturbance load in the tracking control problem whereas considering theoretical demonstrations. By adjusting controller parameters properly, the position and velocity tracking error converge in arbitrary small values. Finally, the effectiveness of the proposed method is verified in two illustrative examples.
Adaptive dynamic programing based optimal control for a robot manipulator Dao Phuong Nam; Nguyen Hong Quang; Tran Phuong Nam; Tran Thi Hai Yen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.397 KB) | DOI: 10.11591/ijpeds.v11.i3.pp1123-1131

Abstract

In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design. 
On finite-time output feedback sliding mode control of an elastic multi-motor system Pham Tuan Thanh; Tran Xuan Tinh; Dao Phuong Nam; Dao Sy Luat; Nguyen Hong Quang
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 12, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v12.i1.pp10-19

Abstract

In this paper, the tracking control scheme is presented using the framework of finite-time sliding mode control (SMC) law and high-gain observer for disturbed/uncertain multi-motor driving systems under the consideration multi-output systems. The convergence time of sliding mode control is estimated in connection with linear matrix inequalities (LMIs). The input state stability (ISS) of proposed controller was analyzed by Lyapunov stability theory. Finally, the extensive simulation results are given to validate the advantages of proposed control design.
Min Max Model Predictive Control for Polysolenoid Linear Motor Nguyen Hong Quang; Nguyen Phung Quang; Nguyen Nhu Hien; Nguyen Thanh Binh
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 | DOI: 10.11591/ijpeds.v9.i4.pp1666-1675

Abstract

The Polysolenoid Linear Motor (PLM) have been playing a crucial role in many industrial aspects because it provides a straight motion directly without mediate mechanical actuators. Some control methods for PLM based on Rotational Motor are applied to obtain several good performances, but position and velocity constraints which are important in real systems are ignored. In this paper, we analysis control problem of tracking position in PLM under state-independent disturbances via min-max model predictive control. The proposed controller brings tracking position error converge to zero and satisfies state including position and velocity and input constraints. The simulation results validity a good efficiency of the proposed controller.
Adaptive dynamic programming algorithm for uncertain nonlinear switched systems Dao Phuong Nam; Nguyen Hong Quang; Nguyen Nhat Tung; Tran Thi Hai Yen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 12, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v12.i1.pp551-557

Abstract

This paper studies an approximate dynamic programming (ADP) strategy of a group of nonlinear switched systems, where the external disturbances are considered. The neural network (NN) technique is regarded to estimate the unknown part of actor as well as critic to deal with the corresponding nominal system. The training technique is simul-taneously carried out based on the solution of minimizing the square error Hamilton function. The closed system’s tracking error is analyzed to converge to an attraction region of origin point with the uniformly ultimately bounded (UUB) description. The simulation results are implemented to determine the effectiveness of the ADP based controller.
Application of model reduction for robust control of self-balancing two-wheeled bicycle Vu Ngoc Kien; Nguyen Hong Quang; Ngo Kien Trung
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16298

Abstract

In recent years, balance control of two-wheeled bicycle has received more attention of scientists. One difficulty of this problem is the control object is unstable and constantly impacted by noise. To solve this problem, the authors often use robust control algorithms. However, robust controller of self-balancing two-wheeled bicycle are often complex and higher order so affect to quality during real controlling. The article introduces the stochastic balanced truncation algorithm based on Schur analysis and applies this algorithm to reduce order higher order robust controller in control balancing two-wheeled bicycle problem. The simulation results show that the reduced 4th and 5th order controller arcoording to the stochastic balanced truncation algorithm based on Schur analysis can control the two-wheeled bicycle model. The reduced 3rd order controller cannot control the balance of the two-wheeled bicycle model. The reduced 4th and 5th order controller can replace the original controller while the performance of the control system is ensured. Using reduced 5th, 4th order controller will make the program code simpler, reducing the calculation time of the self-balancing two-wheel control system. The simulation results show the correctness of the model reduction algorithm and the robust control algorithm of two-wheeled self-balancing two-wheeled bicycle.
Radial basis function neural network control for parallel spatial robot Nguyen Hong Quang; Nguyen Van Quyen; Nguyen Nhu Hien
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 6: December 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i6.14913

Abstract

The derivation of motion equations of constrained spatial multibody system is an important problem of dynamics and control of parallel robots. The paper firstly presents an overview of the calculating the torque of the driving stages of the parallel robots using Kronecker product. The main content of this paper is to derive the inverse dynamics controllers based on the radial basis function (RBF) neural network control law for parallel robot manipulators. Finally,  numerical simulation of the inverse dynamics controller for a 3-RRR delta robot manipulator is presented as an illustrative example.
Experiment based comparative analysis of stator current controllers using predictive current control and proportional integral control for induction motors Vo Thanh Ha; Tran Trong Minh; Nguyen Tung Lam; Nguyen Hong Quang
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (603.926 KB) | DOI: 10.11591/eei.v9i4.2084

Abstract

The stator current control loop plays an important role in ensuring the quality of electric drives interm of producing fast and adequate required torque. When the current controller provides ideal responses, speed control design subsequently is in charge of improving the system performances. Classical PID control is commonly used in current loop design, this paper presents the comparative analysis of current stator controller using proportional integral control and predictive current control (PCC) in field-oriented control-based induction motor drives, with rigidly coupled loads. The experimental results show system responses with PID and PCC. Informative experiment-based analysis provides primary guidance in selection between the two controls. 
Co-Authors Dao Phuong Nam Dao Sy Luat Do Trung Hai Le Ngoc Truc Ngo Kien Trung Nguyen Nhat Tung Nguyen Nhu Hien Nguyen Phung Quang Nguyen Phung Quang Nguyen Phung Quang Nguyen Thanh Binh Nguyen Tung Lam Nguyen Tung Lam Nguyen Van Lanh Nguyen Van Quyen Pham Tuan Thanh Pham Van Tuan Tran Phuong Nam Tran Thi Hai Yen Tran Trong Minh Tran Xuan Tinh Vo Thanh Ha Vo Thanh Ha Vu Ngoc Kien