Neural control and system identification using a similarity approach

Steffen Brueckner; Stephan Rudolph

doi:10.1117/12.388768

19 June 2000 Neural control and system identification using a similarity approach

Steffen Brueckner, Stephan Rudolph

Proceedings Volume 3984, Smart Structures and Materials 2000: Mathematics and Control in Smart Structures; (2000) https://doi.org/10.1117/12.388768
Event: SPIE's 7th Annual International Symposium on Smart Structures and Materials, 2000, Newport Beach, CA, United States

Abstract

For nonlinear and adaptive control of smart structures direct and indirect neural network control strategies have been suggested. In indirect neural network control the identified plant models are usually implemented as black-box neural networks using no a priori knowledge. Designing a neural network for system identification using dimensional analysis results in neural networks, where in contrary to black-box solutions no dimensionally inhomogeneous states can occur. Furthermore, the generalization and learning properties of neural networks designed using dimensional analysis are usually improved compared to conventional black-box networks. This work describes a technique of using neural networks for system identification and control, where the neural network has been constructed according to a dimensional analysis of the governing equations.

Citation Download Citation

Steffen Brueckner and Stephan Rudolph "Neural control and system identification using a similarity approach", Proc. SPIE 3984, Smart Structures and Materials 2000: Mathematics and Control in Smart Structures, (19 June 2000); https://doi.org/10.1117/12.388768

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available