A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Memory Augmented Neural Network Adaptive Controller for Strict Feedback Nonlinear Systems
[article]
2020
arXiv
pre-print
In this work, we consider the adaptive nonlinear control problem for strict feedback nonlinear systems, where the functions that determine the dynamics of the system are completely unknown. We assume that certain upper bounds for the functions g_is of the system are known. The objective of the control design is to design an adaptive controller that can adapt to changes in the unknown functions that are even abrupt. We propose a novel backstepping memory augmented NN (MANN) adaptive control
arXiv:1906.05421v7
fatcat:dfrpysrf7rhgdoaqpemhtzkclm