Discrete-Time Optimal Control via Local Policy Iteration Adaptive Dynamic Programming

In this paper, a discrete-time optimal control scheme is developed via a novel local policy iteration adaptive dynamic programming algorithm. In the discrete-time local policy iteration algorithm, the iterative value function and iterative control law can be updated in a subset of the state space, w...

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Veröffentlicht in:IEEE transactions on cybernetics Jg. 47; H. 10; S. 3367 - 3379
Hauptverfasser: Wei, Qinglai, Liu, Derong, Lin, Qiao, Song, Ruizhuo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.10.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Adaptive algorithms
Adaptive control
Adaptive critic designs
adaptive dynamic programming (ADP)
Algorithms
approximate dynamic programming
Computer simulation
Convergence
Discrete-event systems
Dynamic programming
Heuristic algorithms
Iterative algorithms
Iterative methods
local policy iteration
Markov analysis
neuro-dynamic programming
Nonlinear systems
OptimAL control
Optimization
Servers
Time optimal control
ISSN:2168-2267, 2168-2275
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Zusammenfassung:In this paper, a discrete-time optimal control scheme is developed via a novel local policy iteration adaptive dynamic programming algorithm. In the discrete-time local policy iteration algorithm, the iterative value function and iterative control law can be updated in a subset of the state space, where the computational burden is relaxed compared with the traditional policy iteration algorithm. Convergence properties of the local policy iteration algorithm are presented to show that the iterative value function is monotonically nonincreasing and converges to the optimum under some mild conditions. The admissibility of the iterative control law is proven, which shows that the control system can be stabilized under any of the iterative control laws, even if the iterative control law is updated in a subset of the state space. Finally, two simulation examples are given to illustrate the performance of the developed method.
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ISSN:2168-2267
2168-2275
DOI:10.1109/TCYB.2016.2586082