Virtual Reference Feedback Tuning of MIMO Data-Driven Model-Free Adaptive Control Algorithms

被引：5

作者：

Roman, Raul-Cristian ^{[1
]}

Radac, Mircea-Bogdan ^{[1
]}

Precup, Radu-Emil ^{[1
]}

Petriu, Emil M. ^{[2
]}

机构：

[1] Politehn Univ Timisoara, Timisoara, Romania

[2] Univ Ottawa, Ottawa, ON, Canada

来源：

TECHNOLOGICAL INNOVATION FOR CYBER-PHYSICAL SYSTEMS | 2016年 / 470卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Model-Free Adaptive Control; Optimization; Twin Rotor Aerodynamic System; Virtual Reference Feedback Tuning; SEARCH ALGORITHM; SYSTEMS; DESIGN;

D O I：

10.1007/978-3-319-31165-4_25

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a new tuning approach by which all Model-Free Adaptive Control (MFAC) algorithm parameters are computed using a nonlinear Virtual Reference Feedback Tuning (VRFT) algorithm. This new mixed data-driven control approach, which results in a mixed data-driven tuning algorithm, is advantageous as it offers a systematic way to tune the parameters of MFAC algorithms by VRFT using only the input/output data of the process. The proposed approach is validated by a set of MIMO experiments conducted on a nonlinear twin rotor aerodynamic system laboratory of equipment position control system. The mixed VRFT-MFAC algorithm is compared with a classical MFAC algorithm whose initial parameter values are optimally tuned.

引用

页码：253 / 260

页数：8

共 17 条

[1]

[Anonymous], 2 ROT AER SYST US MA

[2]

Campi MC, 2005, IEEE DECIS CONTR P, P6608

[3] Direct nonlinear control design: The virtual reference feedback tuning (VRFT) approach [J].