Expected value based optimal control for discrete-time stochastic noncausal systems

In this paper, optimal control models subject to two types of discrete-time stochastic noncausal systems are considered in order. The stochastic noncausal systems are stochastic singular systems assumed to be regular alone. Based on the principle of dynamic programming, a recurrence equation is dedu...

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Bibliographic Details
Published inOptimization letters Vol. 16; no. 6; pp. 1847 - 1879
Main Authors Shu, Yadong, Li, Bo
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2022
Subjects
Computational Intelligence
Mathematics
Mathematics and Statistics
Numerical and Computational Physics
Operations Research/Decision Theory
Optimization
Original Paper
Simulation
Recurrence equation
Stochastic noncausal system
Optimal control
Quadratic input
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Summary:In this paper, optimal control models subject to two types of discrete-time stochastic noncausal systems are considered in order. The stochastic noncausal systems are stochastic singular systems assumed to be regular alone. Based on the principle of dynamic programming, a recurrence equation is deduced to simplify the optimal control models. Then, by applying the recurrence equation, a bang-bang optimal control problem ruled by a linear stochastic noncausal system and an optimal control problem for a stochastic noncausal system with quadratic inputs are both solved, and the optimal solutions are presented through analytical expressions. A numerical example is provided to illustrate the effectiveness of the results about the bang-bang optimal control problem.
ISSN:1862-4472
1862-4480
DOI:10.1007/s11590-021-01807-z