• Electronics Optics & Control
  • Vol. 25, Issue 9, 17 (2018)
PU Jun, MA Qing-liang, and GU Fan
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2018.09.004 Cite this Article
    PU Jun, MA Qing-liang, GU Fan. H2/H∞ Control of an Unknown Model Nonlinear System Based on Adaptive Dynamic Programming[J]. Electronics Optics & Control, 2018, 25(9): 17 Copy Citation Text show less

    Abstract

    An online adaptive dynamic programming algorithm is proposed for getting the approximate solution of the coupled Hamilton-Jacobi-Isaacs Equations (HJIE), and obtaining the Nash equilibrium strategy of mixed H2/H∞ control of nonlinear system.By adding the detection signal to the control strategy and the interference strategy, an approximate dynamic programming algorithm is acquired for solving mixed H2/H∞ control problems with unknown model without depending on model information of the system.Two critic neural networks and two executive neural networks are used to synchronously update two value functions, control strategies and interference strategies online.The unknown parameters of the neural network are estimated by generalized least squares.The simulation results verify the feasibility of the algorithm.
    PU Jun, MA Qing-liang, GU Fan. H2/H∞ Control of an Unknown Model Nonlinear System Based on Adaptive Dynamic Programming[J]. Electronics Optics & Control, 2018, 25(9): 17
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