@article{60a278e41a624061a2d036ab738b6c66,
title = "Upper Bounds for Approximation of Continuous-Time Dynamics Using Delayed Outputs and Feedforward Neural Networks",
abstract = "The problem of approximation of unknown dynamics of a continuous-time observable nonlinear system is considered using a feedforward neural network, operating over delayed sampled outputs of the system. Error bounds are derived that explicitly depend upon the sampling time interval and network architecture. The main result of this note broadens the class of nonlinear dynamical systems for which adaptive output feedback control and state estimation problems are solvable.",
keywords = "Adaptive estimation, Adaptive output feedback, Approximation, Continuous-time dynamics, Feedforward neural networks",
author = "Eugene Lavretsky and Naira Hovakimyan and Calise, {Anthony J.}",
note = "Funding Information: Manuscript received July 13, 2002; revised January 9, 2003 and April 22, 3003. Recommended by Associate Editor T. Parisini. The work of N. Hov-akimyan and A. J. Calise was supported by the Air Force Office of Scientific Research under Contract F4960-01-1-0024. E. Lavretsky is with Phantom Works, The Boeing Company, Huntington Beach, CA 92648 USA (e-mail: eugene.lavretsky@boeing.com). N. Hovakimyan is with the Department of Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061 USA (e-mail: nhovakim@vt.edu). A. J. Calise is with the School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA (e-mail: anthony.calise@ae.gatech.edu). Digital Object Identifier 10.1109/TAC.2003.816987 1For simplicity, we consider here only the single-input–single-output (SISO) case.",
year = "2003",
month = sep,
doi = "10.1109/TAC.2003.816987",
language = "English (US)",
volume = "48",
pages = "1606--1610",
journal = "IRE Transactions on Automatic Control",
issn = "0018-9286",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "9",
}