On-line direct control design for nonlinear systems

被引：1

作者：

Tanaskovic, Marko ^{[1
]}

Fagiano, Lorenzo ^{[2
]}

Novara, Carlo ^{[3
]}

Morari, Manfred ^{[1
]}

机构：

[1] Swiss Fed Inst Technol, Automat Control Lab, Phys Str 3, Zurich, Switzerland

[2] ABB Switzerland Ltd, Corp Res, CH-5405 Baden, Switzerland

[3] Politecn Torino, Dipartimento Automat & Informat, I-10129 Turin, Italy

来源：

IFAC PAPERSONLINE | 2015年 / 48卷 / 28期

关键词：

Data-driven control; nonlinear systems; direct control; dynamic inversion; stability;

D O I：

10.1016/j.ifacol.2015.12.115

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An approach to design a feedback controller for nonlinear systems directly from experimental data is presented. Improving over a recently proposed technique, which employs exclusively a batch of experimental data collected in a preliminary experiment, here the control law is updated and refined during real-time operation, hence enabling an on-line learning capability. The theoretical properties of the described approach, in particular closed-loop stability and tracking accuracy, are discussed. Finally, the experimental results obtained with a water tank laboratory setup are presented.

引用

页码：144 / 149

页数：6

共 50 条

[21] SURVEY OF ON-LINE CONTROL COMPUTER SYSTEMS
KOMPASS, EJ
[J]. CONTROL ENGINEERING, 1972, 19 (01) : 52 - &
[22] On-line modeling for emergency control systems
Kojima, Y
Taoka, H
Oshida, H
Goda, T
[J]. CONTROL OF POWER SYSTEMS AND POWER PLANTS 1997 (CPSPP'97), 1998, : 627 - 632
[23] Comparison between three types of iterative learning control for nonlinear systems: on-line, off-line and on-line taking into account the previous error
Bouakrif, Farah
[J]. 2014 INTERNATIONAL CONFERENCE ON ELECTRICAL SCIENCES AND TECHNOLOGIES IN MAGHREB (CISTEM), 2014,
[24] An on-line PID control scheme for unknown nonlinear dynamic systems using evolution strategy
Park, JH
Choi, YK
[J]. 1996 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION (ICEC '96), PROCEEDINGS OF, 1996, : 759 - 763
[25] On-line tuning of fuzzy-neural network for adaptive control of nonlinear dynamical systems
Leu, YG
Lee, TT
Wang, WY
[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1997, 27 (06): : 1034 - 1043
[26] On-line approximation based control of uncertain nonlinear systems with magnitude, rate and bandwidth constraints
Farrell, J
Polycarpou, M
Sharma, M
[J]. PROCEEDINGS OF THE 2004 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2004, : 2557 - 2562
[27] ON-LINE CONTROL OF CUTTING CONDITIONS USING DIRECT FEEDBACK
SHILLAM, NF
[J]. MACHINERY AND PRODUCTION ENGINEERING, 1971, 119 (3074): : 561 - &
[28] On-line parametric identification of MDOF nonlinear hysteretic systems
Smyth, AW
Masri, SF
Chassiakos, AG
Caughey, TK
[J]. JOURNAL OF ENGINEERING MECHANICS, 1999, 125 (02) : 133 - 142
[29] A new on-line modeling approach to nonlinear dynamic systems
Liu, Shirong
Yu, Qijiang
Yu, Jinshou
[J]. ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 2, PROCEEDINGS, 2006, 3972 : 771 - 776
[30] On-line robust fault detection in a class of nonlinear systems
Liu, C.S.
Wang, F.
Hu, S.S.
[J]. Nanjing Hangkong Hangtian Daxue Xuebao/Journal of Nanjing University of Aeronautics and Astronautics, 2001, 33 (03):

← 1 2 3 4 5 →