Modern Control Engineering
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Expert Systems with Applications: An International Journal
Gaussian networks for direct adaptive control
IEEE Transactions on Neural Networks
Three-layer feedforward structures smoothly approximating polynomial functions
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
Adaptive dissolved oxygen control based on dynamic structure neural network
Applied Soft Computing
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In this paper, design, dynamic modeling and control of the fabricated underwater remotely operated vehicle have been considered. Dynamic model of the vehicle is presented for four degrees of freedom and an accurate representation of the dynamic effects of the towed cable is used for dynamic simulation and control design. A nonlinear adaptive neural network controller is developed and simulated. Multi-layer and radial basis function neural networks are used for designing the adaptive controllers. Finally, the performance of the vehicle with neural network controllers is compared with a PD controller. The significant improvement is observed for tracking performance of the vehicle in all controllable degrees of freedom. Also, the simulation illustrated the robustness of controllers for the relative large distributions of the communication cable.