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Volume 6 Issue 3
May  2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2019  >  6(3): 657-666
Ruizhuo Song and Liao Zhu, "Optimal Fixed-Point Tracking Control for Discrete-Time Nonlinear Systems via ADP," IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 657-666, May 2019. doi: 10.1109/JAS.2019.1911453
Citation: Ruizhuo Song and Liao Zhu, "Optimal Fixed-Point Tracking Control for Discrete-Time Nonlinear Systems via ADP," IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 657-666, May 2019. doi: 10.1109/JAS.2019.1911453
shu

Optimal Fixed-Point Tracking Control for Discrete-Time Nonlinear Systems via ADP

doi: 10.1109/JAS.2019.1911453

  • School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China

Funds:

the National Natural Science Foundation of China 61873300

the National Natural Science Foundation of China 61722312

the Fundamental Research Funds for the Central Universities FRF-GF-17-B45

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    Abstract
  • Based on adaptive dynamic programming (ADP), the fixed-point tracking control problem is solved by a value iteration (Ⅵ) algorithm. First, a class of discrete-time (DT) nonlinear system with disturbance is considered. Second, the convergence of a Ⅵ algorithm is given. It is proven that the iterative cost function precisely converges to the optimal value, and the control input and disturbance input also converges to the optimal values. Third, a novel analysis pertaining to the range of the discount factor is presented, where the cost function serves as a Lyapunov function. Finally, neural networks (NNs) are employed to approximate the cost function, the control law, and the disturbance law. Simulation examples are given to illustrate the effective performance of the proposed method.

     

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