Adaptive Dynamic Programming for Stochastic Systems With State and Control Dependent Noise

Tao Bian; Yu Jiang; Zhong Ping Jiang

doi:10.1109/TAC.2016.2550518

Adaptive Dynamic Programming for Stochastic Systems With State and Control Dependent Noise

Tao Bian, Yu Jiang, Zhong Ping Jiang

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In this technical note, the adaptive optimal control problem is investigated for a class of continuous-time stochastic systems subject to multiplicative noise. A novel non-model-based optimal control design methodology is employed to iteratively update the control policy on-line by using directly the data of the system state and input. Both adaptive dynamic programming (ADP) and robust ADP algorithms are developed, along with rigorous stability and convergence analysis. The effectiveness of the obtained methods is illustrated by an example arising from biological sensorimotor control.

Original language	English (US)
Article number	7447723
Pages (from-to)	4170-4175
Number of pages	6
Journal	IEEE Transactions on Automatic Control
Volume	61
Issue number	12
DOIs	https://doi.org/10.1109/TAC.2016.2550518
State	Published - Dec 2016

Keywords

Adaptive dynamic programming
adaptive optimal control
stochastic systems

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TAC.2016.2550518

Cite this

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abstract = "In this technical note, the adaptive optimal control problem is investigated for a class of continuous-time stochastic systems subject to multiplicative noise. A novel non-model-based optimal control design methodology is employed to iteratively update the control policy on-line by using directly the data of the system state and input. Both adaptive dynamic programming (ADP) and robust ADP algorithms are developed, along with rigorous stability and convergence analysis. The effectiveness of the obtained methods is illustrated by an example arising from biological sensorimotor control.",

keywords = "Adaptive dynamic programming, adaptive optimal control, stochastic systems",

author = "Tao Bian and Yu Jiang and Jiang, {Zhong Ping}",

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language = "English (US)",

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Adaptive Dynamic Programming for Stochastic Systems With State and Control Dependent Noise

Abstract

Keywords

ASJC Scopus subject areas

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