Abstract
This paper addresses an on-line approximation-based robust adaptive control problem for the automatic train operation (ATO) system under actuator saturation caused by constraints from serving motors. A robust adaptive control law is proposed, which is proved capable of on-line estimating of the unknown system parameters and stabilizing the closed-loop system. To cope with actuator saturation, another robust adaptive control is proposed for the ATO system, by explicitly considering the actuator saturation nonlinearity other than unknown system parameters, which is also proved capable of stabilizing the closed-loop system. Simulation results are presented to verify the effectiveness of the two proposed control laws. © 2000-2011 IEEE.
| Original language | English |
|---|---|
| Article number | 6549162 |
| Pages (from-to) | 1733-1742 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 14 |
| Issue number | 4 |
| Online published | 28 Jun 2013 |
| DOIs | |
| Publication status | Published - Dec 2013 |
Research Keywords
- Actuator saturation
- Automatic train operation (ATO)
- Neural network
- Robust adaptive control
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