Novel 1 neural network adaptive control architecture with guaranteed transient performance

Chengyu Cao, Naira Hovakimyan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we present a novel neural network adaptive control architecture with guaranteed transient performance. With this new architecture both input and output signals of an uncertain nonlinear system follow a desired linear system during the transient phase, in addition to stable tracking. This new architecture uses a low-pass filter in the feedback-loop, which consequently enables to enforce the desired transient performance by increasing the adaptation gain. For the guaranteed transient performance of both input and output signals of the uncertain nonlinear system, the 1 gain of a cascaded system, comprised of the low-pass filter and the closed-loop desired reference model, is required to be less than the inverse of the Lipschitz constant of the unknown nonlinearities in the system. The tools from this paper can be used to develop a theoretically justified verification and validation framework for neural network adaptive controllers. Simulation results illustrate the theoretical findings.

Original languageEnglish (US)
Title of host publication2007 European Control Conference, ECC 2007
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1334-1339
Number of pages6
ISBN (Electronic)9783952417386
StatePublished - Jan 1 2007
Externally publishedYes
Event2007 9th European Control Conference, ECC 2007 - Kos, Greece
Duration: Jul 2 2007Jul 5 2007

Publication series

Name2007 European Control Conference, ECC 2007

Other

Other2007 9th European Control Conference, ECC 2007
CountryGreece
CityKos
Period7/2/077/5/07

ASJC Scopus subject areas

  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'Novel <sub>1</sub> neural network adaptive control architecture with guaranteed transient performance'. Together they form a unique fingerprint.

Cite this