Application of Conditional-Optimal Filter for Synthesis of Suboptimal Control in the Problem of Optimizing the Output of a Nonlinear Differential Stochastic System

We propose a suboptimal solution for the control problem for the Ito diffusion process and linear controlled output with a quadratic quality criterion for the case of indirect observations of the state. We use the previously obtained solution of the problem with complete information, the concept of...

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Bibliographic Details
Published in:Automation and remote control Vol. 81; no. 11; pp. 1963 - 1973
Main Author: Bosov, A. V.
Format: Journal Article
Language:English
Published: Moscow Pleiades Publishing 01.11.2020
Subjects:
639/301/1034/1035
639/925/357/995
CAE) and Design
Calculus of Variations and Optimal Control; Optimization
Computer-Aided Engineering (CAD
Control
Mathematics
Mathematics and Statistics
Mechanical Engineering
Mechatronics
Robotics
Systems Theory
Topical-Issue
stochastic differential system
stochastic filtering
Monte Carlo method
optimal control
stochastic differential equation
conditionally optimal filtering
ISSN:0005-1179, 1608-3032
Online Access:Get full text
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Summary:We propose a suboptimal solution for the control problem for the Ito diffusion process and linear controlled output with a quadratic quality criterion for the case of indirect observations of the state. We use the previously obtained solution of the problem with complete information, the concept of separation between control and filtering problems, and the method of conditionally optimal filtering developed by V.S. Pugachev. We propose an alternative to the traditional practical approach for the synthesis of suboptimal control in a problem with incomplete information, which consists in a formal substitution in the solution of a state with its estimate. Instead of the problem of optimizing the output generated by the original model of the differential equation, we use as the state an estimate of a conditionally optimal filter. We develop one version of the numerical implementation of the proposed algorithm based on the Monte Carlo method and computer simulation.
ISSN:0005-1179
1608-3032
DOI:10.1134/S0005117920110028