Tracking control of multi-input affine nonlinear dynamical systems with unknown nonlinearities using dynamical neural networks
- 1 April 1999
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
- Vol. 29 (2) , 179-189
- https://doi.org/10.1109/3477.752792
Abstract
The purpose of this paper is to design and rigorously analyze a tracking controller, based on a dynamic neural network model for unknown but affine in the control, multi input nonlinear dynamical systems, Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. The controller derived is smooth. No a priori knowledge of an upper bound on the "optimal" weights and modeling errors is required. Simulation studies are used, to illustrate and clarify the theoretical results.Keywords
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