A Parallel Robust Model Reference Control Method Based on Neural Network
- Resource Type
- Conference
- Authors
- Jin, Lv; Chen, Guo
- Source
- 2007 IEEE International Conference on Control and Automation Control and Automation, 2007. ICCA 2007. IEEE International Conference on. :1377-1380 May, 2007
- Subject
- Robotics and Control Systems
Computing and Processing
Signal Processing and Analysis
Robust control
Neural networks
Marine vehicles
Motion control
Adaptive control
Robust stability
Automatic control
Automation
Nonlinear control systems
Data engineering
nonlinear control
neural network
ship motion control
model reference control
robust confrol
- Language
- ISSN
- 1948-3449
1948-3457
Aiming to the control feature of large ship, a neural network parallel self-learning robust model reference control method of ship course is presented. The problems of model online identification and controller online design in traditional adaptive control is solved by this compounded control structure using the self-learning and nonlinear map capability of neural network, so that the high precision output track control of uncertain nonlinear large ship can be realized. Furthermore, a robust feedback controller is imported to ensure closed-loop stability in the initial learning stages of NN model and improve the NN control's real-time ability. Simulation results show that the method had perfect control effect.