Open AccessSampled‐data‐based adaptive optimal output‐feedback control of a 2‐degree‐of‐freedom helicopter
Author(s) -
Gao Weinan,
Huang Mengzhe,
Jiang ZhongPing,
Chai Tianyou
Publication year - 2016
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.0977
Subject(s) - control theory (sociology) , convergence (economics) , bounded function , controller (irrigation) , adaptive control , computer science , dynamic programming , degree (music) , optimal control , control (management) , output feedback , sampling (signal processing) , mathematical optimization , mathematics , algorithm , artificial intelligence , physics , acoustics , mathematical analysis , filter (signal processing) , agronomy , economics , computer vision , biology , economic growth
This study addresses the adaptive and optimal control problem of a Quanser's 2‐degree‐of‐freedom helicopter via output feedback. In order to satisfy the requirement of digital implementation of flight controller, this study distinguishes itself through proposing a novel sampled‐data‐based approximate/adaptive dynamic programming approach. A policy iteration algorithm is presented that yields to learn a near‐optimal control gain iteratively by input/output data. The convergence of the proposed algorithm is theoretically ensured and the trade‐off between the optimality and the sampling period is rigorously studied as well. Finally, the authors show the performance of the proposed algorithm under bounded model uncertainties.