Neural Network Engineering in Dynamic Control Systems: Advances in Industrial Control
Neural Network Engineering in Dynamic Control Systems: Advances in Industrial Control
Neuro-Control Systems: Theory and Applications
Neuro-Control Systems: Theory and Applications
Nonlinear adaptive trajectory tracking using dynamic neural networks
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Neural block control for synchronous generators
Engineering Applications of Artificial Intelligence
Hi-index | 22.14 |
By modifying some previously developed results for nonlinear identification and control using recurrent neural networks, the present authors propose a new neural network identifier in block form, and, based on this model, a control law is developed by combining sliding mode and block controls. This neural identifier and control law allow satisfactory trajectory tracking for general nonlinear systems. Applicability of the new design is illustrated, via simulations, for robust tracking control of stepping motors.