Ship Track Adaptive Control Using Error Estimator
- Resource Type
- Conference
- Authors
- Zhang, Gui-Chen; Ren, Guang
- Source
- 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on. 1:639-644 Oct, 2008
- Subject
- Computing and Processing
Marine vehicles
Adaptive control
Error correction
Control systems
Automatic control
Sliding mode control
Multilayer perceptrons
Neural networks
Multi-layer neural network
Trajectory
Ship
Track control
course control
multilayer perceptrons neural network
extended Kalman filter
error estimator
- Language
The error estimator control scheme for ship track with unknown dynamics is proposed in this paper. The control scheme is based on a multilayer perceptrons neural network (MLPNN) of the ship. The MLPNN is adapted by an extended Kalman filter (EKF) to learn ship's dynamics changes. Therefore, the autopilot output is guaranteed to converge to the desired trajectory asymptotically, and the ship also tracks the desired trajectory due to error estimator. The proposed scheme is evaluated by applying it to a simulated continuous ship's movement process.