Model reference adaptive control of nonlinear dynamical systems using multilayer neural networks
- 17 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 7, 4766-4771
- https://doi.org/10.1109/icnn.1994.375046
Abstract
A multilayer discrete-time neural net (NN) controller is presented for the model reference adaptive control of a class of MIMO dynamical systems. No initial learning phase is needed and the tracking error between the output of the nonlinear plant and a linear model converges within a very short time. This weight tuning paradigm is based on the well-known delta rule but includes a modification to the learning rate parameter plus a correction term. It guarantees tracking as well as bounded NN weights in non-ideal situations, so that a persistency of excitation condition on the internal signals is not needed. Simulation results are presented in order to verify the theoretical conclusions.<>Keywords
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