Title :
Adaptive control using neural networks and approximate models
Author :
Narendra, Kumpati S. ; Mukhopadhyay, Snehasis
Author_Institution :
Center for Syst. Sci., Yale Univ., New Haven, CT, USA
Abstract :
The NARMA model is an exact representation of the input-output behavior of dynamical systems. However, it is not convenient for purposes of control. In this paper, the authors introduce two classes of models which are approximations to the NARMA model, and at the same time substantially simplifies the control problem
Keywords :
adaptive control; autoregressive moving average processes; discrete time systems; multidimensional systems; neural nets; nonlinear dynamical systems; NARMA model; adaptive control; approximate models; dynamical systems; input-output behavior; neural networks; Adaptive control; Books; Control systems; Integrated circuit modeling; Mathematical model; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Process control;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.529269
