Application of neural networks in robotic control

Simulations of a 5-link robotic manipulator using both conventional model-based and neural network controllers have been performed. Final position errors of the joints for various load deviations are used to measure the controller performance. Results indicated that, due to its adaptive capability, the neural network controller yields a smaller error for all joints except joint number 5 as compared to the model-based controller