Adaptive robust neural controller for robots
✍ Scribed by S̨ahin Yıldırım
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 154 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0921-8890
No coin nor oath required. For personal study only.
✦ Synopsis
This paper presents an investigation on the trajectory control of a robot using a new type of recurrent neural network. A three-layered recurrent neural network is employed to estimate the forward dynamics model of the robot. Standard backpropagation (BP) algorithm is used as a learning algorithm for this network to minimise the difference between the robot actual response and that predicted by the neural network. This algorithm is employed to update the connection weights of the neural network controller with three layers using a gradient function.
📜 SIMILAR VOLUMES
In this paper we present a robust adaptive control scheme for robot manipulators with time-varying parameters and unmodeled dynamics. Our scheme ensures that all signals in the closed-loop robot system are bounded and the tracking error is of the order of the parameter variations and unmodeled dynam