Adaptive backstepping controller and sliding mode controller design for formation flight in Sun–Earth L 2 point

2016 ◽  
Vol 55 ◽  
pp. 409-418 ◽  
Author(s):  
Feng Wang ◽  
Ming Liu ◽  
Rongyu Jin ◽  
Zhuoshi Li
Keyword(s):  
Controller Design ◽  
Sliding Mode ◽  
Formation Flight ◽  
Sliding Mode Controller ◽  
Adaptive Backstepping ◽  
Backstepping Controller ◽  
Adaptive Backstepping Controller

Nonlinear Adaptive Backstepping Controller Design for Three-Phase Grid-Connected Solar Photovoltaic Systems

2017 ◽  
Vol 45 (20) ◽  
pp. 2275-2292 ◽  
Author(s):  
Tushar Kanti Roy ◽  
Md Apel Mahmud ◽  
Amanullah Maung Than Oo ◽  
Ramesh Bansal ◽  
Md Enamul Haque
Keyword(s):  
Controller Design ◽  
Photovoltaic Systems ◽  
Solar Photovoltaic ◽  
Adaptive Backstepping ◽  
Three Phase ◽  
Backstepping Controller ◽  
Adaptive Backstepping Controller

ADAPTIVE BACKSTEPPING SLIDING MODE CONTROLLER FOR FLIGHT SIMULATOR BASED ON RBFNN

2013 ◽  
Vol 04 (04) ◽  
pp. 1342007 ◽  
Author(s):  
YUNJIE WU ◽  
BAITING LIU ◽  
WULONG ZHANG ◽  
XIAODONG LIU
Keyword(s):  
Controller Design ◽  
Sliding Mode ◽  
Flight Simulator ◽  
Sliding Mode Controller ◽  
Control Input ◽  
Adaptive Backstepping ◽  
External Disturbances ◽  
Base Function ◽  
System A ◽  
Radial Base Function

For flight simulator system, a kind of Adaptive Backstepping Sliding Mode Controller (ABSMC) based on Radial Base Function Neural Network (RBFNN) observer is presented. The sliding mode control theory is famous by its characteristic that it is insensitive to the external disturbances and parameters uncertainties. Combining this characteristic with Backstepping method can simplifies the controller design. And the addition of the terminal attractor can make the arrival time shorten greatly. However, too large external disturbances and parameters uncertainties are still not allowed to the system, and the design process of ABSMC does not have the upper bound information of disturbance until a RBFNN observer is designed to solve the problems. The simulation results show that the proposed scheme can improve the tracking precision and reduce the chattering of the control input, and the system has a higher robustness.

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