System identification: theory for the user
System identification: theory for the user
Dynamics and Control
Ten lectures on wavelets
Neural Computation
Adaptive control of chaos in Lorenz system
Dynamics and Control
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Systems for Control
Wavelet neural networks for function learning
IEEE Transactions on Signal Processing
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Using wavelet network in nonparametric estimation
IEEE Transactions on Neural Networks
Inherent features of wavelets and pulse coupled networks
IEEE Transactions on Neural Networks
Multiwavelet neural network and its approximation properties
IEEE Transactions on Neural Networks
Robust Adaptive Observer Design for Uncertain Systems With Bounded Disturbances
IEEE Transactions on Neural Networks
Accuracy analysis for wavelet approximations
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Nonlinear discrete time neural network observer
Neurocomputing
An observer-based adaptive neural network tracking control of robotic systems
Applied Soft Computing
| Hi-index | 0.00 |
State estimation for uncertain systems affected by external noises is an important problem in control theory. This paper deals with a state observation problem when the dynamic model of a plant contains uncertainties or it is completely unknown. Differential neural network (NN) approach is applied in this uninformative situation but with activation functions described by wavelets. A new learning law, containing an adaptive adjustment rate, is suggested to imply the stability condition for the free parameters of the observer. Nominal weights are adjusted during the preliminary training process using the least mean square (LMS) method. Lyapunov theory is used to obtain the upper bounds for the weights dynamics as well as for the mean squared estimation error. Two numeric examples illustrate this approach: first, a nonlinear electric system, governed by the Chua's equation and second the Lorentz oscillator. Both systems are assumed to be affected by external perturbations and their parameters are unknown.