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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control)
Nguyen Nhu Hien
Thai Nguyen University of Technology
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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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.
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.
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.
Co-Authors Do Trung Hai Nguyen Hong Quang Nguyen Phung Quang Nguyen Thanh Binh Nguyen Van Quyen