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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Tran Thi Hai Yen
Thai Nguyen University of Technology
Control & Systems Engineering Electrical & Electronics Engineering

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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. 
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.
Co-Authors Dao Phuong Nam Nguyen Hong Quang Nguyen Nhat Tung Tran Phuong Nam