Lebesgue-Sampling-Based Optimal Control Problems With Time Aggregation.

CONTROL theory (Engineering); MEASURE theory; STATISTICAL sampling; MARKOV processes; MATHEMATICAL models; REINFORCEMENT learning; DECISION making; PERFORMANCE evaluation; ALGORITHMS; BOUNDARY value problems

We formulate the Lebesgue-sampling-based optimal control problem. We show that the problem can be solved by the time aggregation approach in Markov decision processes (MDP) theory. Policy-iteration-based and reinforcement-learning-based methods are developed for the optimal policies. Both analytical solutions and sample-path-based algorithms are given. Compared to the periodic-sampling scheme, the Lebesgue sampling scheme improves system performance. [ABSTRACT FROM AUTHOR]

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