Optimal fixed-point tracking control for discrete-time nonlinear systems via ADP

Based on adaptive dynamic programming &#x0028 ADP &#x0029, the fixed-point tracking control problem is solved by a value iteration &#x0028 VI &#x0029 algorithm. First, a class of discrete-time &#x0028 DT &#x0029 nonlinear system with disturbance is considered. Second, the con...

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Bibliographic Details
Published in:IEEE/CAA journal of automatica sinica 2019-05, Vol.6 (3), p.657-666
Main Authors: Song, Ruizhuo, Zhu, Liao
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Computer simulation
Control theory
Convergence
Cost function
Discrete time systems
Dynamic programming
Games
Iterative algorithms
Liapunov functions
Mathematical model
Neural networks
Nonlinear control
Nonlinear systems
Optimal control
Tracking control
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Summary:Based on adaptive dynamic programming &#x0028 ADP &#x0029, the fixed-point tracking control problem is solved by a value iteration &#x0028 VI &#x0029 algorithm. First, a class of discrete-time &#x0028 DT &#x0029 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 &#x0028 NNs &#x0029 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.
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2019.1911453