Adaptive dynamic programming algorithm for uncertain nonlinear switched systems

Dao Phuong Nam (Hanoi University of Science and Technology)
Nguyen Hong Quang (Thai Nguyen University of Technology)
Nguyen Nhat Tung (Electric Power University)
Tran Thi Hai Yen (Thai Nguyen University of Technology)

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 12, No 1: March 2021

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.