Adaptive control of nonlinear systems using neural networks
- 1 June 1992
- journal article
- research article
- Published by Taylor & Francis in International Journal of Control
- Vol. 55 (6) , 1299-1317
- https://doi.org/10.1080/00207179208934286
Abstract
Layered networks are used in a nonlinear adaptive control problem. The plant is an unknown feedback-linearizable discrete-time system, represented by an input-output model. A state space model of the plant is obtained to define the zero dynamics, which are assumed to be stable. A linearizing feedback control is derived in terms of some unknown nonlinear functions. To identify these functions, it is assumed that they can be modelled by layered neural networks. The weights of the networks are updated and used to generate the control. A local convergence result is given. Computer simulations verify the theoretical result.This publication has 12 references indexed in Scilit:
- Adaptive Control of Nonlinear Systems Using Neural Networks - A Dead-Zone ApproachPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Back-propagation neural networks for nonlinear self-tuning adaptive controlIEEE Control Systems Magazine, 1990
- Identification and control of dynamical systems using neural networksIEEE Transactions on Neural Networks, 1990
- Adaptive regulation of nonlinear systems with unmodeled dynamicsIEEE Transactions on Automatic Control, 1989
- Nonlinear Control SystemsPublished by Springer Nature ,1989
- Theory of the backpropagation neural networkPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- On the approximate realization of continuous mappings by neural networksNeural Networks, 1989
- Multilayer feedforward networks are universal approximatorsNeural Networks, 1989
- Adaptive control of linearizable systemsIEEE Transactions on Automatic Control, 1989
- A multilayered neural network controllerIEEE Control Systems Magazine, 1988