Abstract
In this paper an adaptive non-singular fast terminal sliding mode (NFTSM) control scheme is proposed to control the electro-mechanical actuator (EMA) in an electric braking system which is a complex electro-mechanical system. In order to realize high-performance brake pressure servo control, a radial basis function (RBF) neural network method is adopted to deal with the difficulty of estimating the upper bound of the compound disturbance in the system, to reduce the conservatism of the design of sliding mode switching gain, and effectively eliminate sliding mode chattering. The simulation results show that, compared with a linear controller, the proposed control strategy is able to improve the servo performance and control precision. In addition the response speed of the braking actuator is enhanced significantly, without changing the traditional double-loop control structure.
| Original language | English |
|---|---|
| Article number | 1637 |
| Journal | Energies |
| Volume | 10 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Chattering
- Electro-mechanical actuator
- RBF neural network
- Terminal sliding mode control
Fingerprint
Dive into the research topics of 'Adaptive nonsingular fast terminal sliding mode control for braking systems with electro-mechanical actuators based on radial basis function'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver