Decentralized control of large-scale systems using single hidden layer neural networks

Author

Nardi, Flavio ; Hovakimyan, Naira ; Calise, Anthony J.

Author_Institution

Sch. of Aerosp. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

4

fYear

2001

fDate

2001

Firstpage

3122

Abstract

A decentralized adaptive control design procedure for large-scale uncertain systems is developed using Single Hidden Layer neural networks. The subsystems are assumed to be feedback linearizable and non-affine in the control, and their interconnections bounded linearly by the tracking error norms. Single Hidden Layer neural networks are introduced to approximate the feedback linearization error signal online from available measurements. A robust adaptive signal is required in the analysis to shield the feedback linearizing control law from the interconnection effects. The tracking errors are shown to be uniformly ultimately bounded, and all other signals uniformly bounded. The proposed adaptive algorithm is implemented in simulation to stabilize an interconnected double inverted pendulum

Keywords

adaptive control; decentralised control; large-scale systems; neural nets; neurocontrollers; uncertain systems; decentralized adaptive control; feedback linearization error signal; large-scale uncertain systems; neural networks; robust adaptive signal; Adaptive control; Distributed control; Error correction; Large-scale systems; Linear approximation; Linear feedback control systems; Neural networks; Neurofeedback; Robust control; Uncertain systems;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2001. Proceedings of the 2001

Conference_Location

Arlington, VA

ISSN

0743-1619

Print_ISBN

0-7803-6495-3

Type

conf

DOI

10.1109/ACC.2001.946400

Filename

946400