Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Stability and approximator convergence in nonparametric nonlinear adaptive control
IEEE Transactions on Neural Networks
Nonlinear adaptive trajectory tracking using dynamic neural networks
IEEE Transactions on Neural Networks
Adaptive observer backstepping control using neural networks
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Gaussian networks for direct adaptive control
IEEE Transactions on Neural Networks
Adaptive neural control for output feedback nonlinear systems using a barrier Lyapunov function
IEEE Transactions on Neural Networks
Improved Output Tracking of a Flexible-Joint Arm using Neural Networks
Neural Processing Letters
| Hi-index | 22.14 |
The paper is extending output feedback nonlinear control and backstepping approaches to a class of systems approximately diffeomorphic to output feedback systems that include unknown functions. The unknown functions are addressed via online function approximation, which results in two types of uncertainty. Parametric uncertainty due to online function approximation and non-parametric uncertainty. The non-parametric uncertainty results from the inability of any function approximator to perfectly model an unknown function and from terms unmodeled by the output feedback form. The non-parametric terms are assumed to be bounded by unknown constants. The backstepping procedure is applied to adapt with respect to both parametric uncertainties and the upper bound on the non-parametric uncertainties.