Title :
Reconstruction of nonlinear systems using delay lines and feedforward networks
Author :
Elliott, David L.
Author_Institution :
Inst. for Syst. Res., Maryland Univ., College Park, MD, USA
Abstract :
Nonlinear system theory ideas have led to a method for approximating the dynamics of a nonlinear system in a bounded region of its state space, by training a feedforward neural network which is then reconfigured in recursive mode to provide a stand-alone simulator of the system. The input layer of the neural network contains time-delayed samples of one or more system outputs and control inputs. Autonomous systems can be simulated in this way by providing impulse inputs
Keywords :
delays; dynamics; feedforward neural nets; identification; nonlinear systems; state-space methods; delay lines; dynamics; feedforward neural networks; identification; nonlinear system reconstruction; recursive mode; state space; time-delayed samples; Adaptive filters; Computer networks; Concurrent computing; Delay lines; Feedforward neural networks; Linear systems; Neural networks; Nonlinear filters; Nonlinear systems; Polynomials;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.529372
