Title

Adaptive Optimal Output Regulation of Time-Delay Systems via Measurement Feedback

Document Type

Article

Publication Date

7-24-2018

Publication Title

IEEE Transactions on Neural Network and Learning Systems

DOI

10.1109/TNNLS.2018.2850520

ISSN

2162-2388

Abstract

This brief proposes a novel solution to problems related to the measurement feedback adaptive optimal output regulation of discrete-time linear systems with input time-delay. Based on reinforcement learning and adaptive dynamic programming, an approximate optimal control policy is obtained via recursive numerical algorithms using online information. Convergence proofs for the proposed algorithms are given. Notably, the exact knowledge of the plant and the exosystem is not needed. The learned control policy is only a function of retrospective input and measurement output data. Theoretical analysis and an application to a grid-connected inverter show that the proposed methodologies serve as effective tools for solving adaptive and optimal output regulation problems.

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