Modified -Policy Iteration Based Adaptive Dynamic Programming for Unknown Discrete-Time Linear Systems

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS(2024)

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摘要
this article, the 1-policy iteration (1-PI) method for the optimal control problem of discrete-time linear systems is reconsidered and restated from a novel aspect. First, the traditional 1-PI method is recalled, and some new properties of the traditional 1-PI are proposed. Based on these new properties, a modified 1-PI algorithm is introduced with its convergence proven. Compared with the existing results, the initial con-dition is further relaxed. The data-driven implementation is then constructed with a new matrix rank condition for veri-fying the feasibility of the proposed data-driven implementation. A simulation example verifies the effectiveness of the proposed method.
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关键词
Adaptive dynamic programming (ADP),data-driven control,discrete-time systems,modified 1-policy iteration (1-PI),policy iteration,unknown systems
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