DocumentCode :
643670
Title :
Sliding modes robust control for electrohydraulic servo system
Author :
Zhaohui Yuan ; Ming Yuan
Author_Institution :
Dept. of Autom., Univ. of Northwestern Polytech., Xian, China
fYear :
2013
fDate :
5-8 Aug. 2013
Firstpage :
1
Lastpage :
6
Abstract :
This document explains the uncertain-nonlinear-system´control problem. I present a robust adaptive sliding mode control, combing the Backstepping algorithm with sliding mode control. Design sliding mode control recursive rules, and then get the virtual control value. By the time, CMAC neural network learns system´ uncertainty as well as the derivative information of each order virtual control value Real-time. The conventional sliding mode control easily leads to chattering as the result of using sign function as switching function. So, we use hyperbolic tangent function instead of sign function as sliding mode switching function, to avoid the possible chattering problem owing to discontinuous terms. Finally, the proposed control algorithm is verified by simulation, within the mathematical model of electric hydraulic servo system.
Keywords :
adaptive control; control system synthesis; electrohydraulic control equipment; electrohydrodynamics; mathematical analysis; neurocontrollers; nonlinear control systems; robust control; servomechanisms; uncertain systems; variable structure systems; CMAC neural network; backstepping algorithm; chattering problem; control algorithm; derivative information; discontinuous terms; electric hydraulic servo system; electrohydraulic servo system; hyperbolic tangent function; mathematical model; robust adaptive sliding mode control; sign function; sliding mode control recursive rules design; sliding mode switching function; uncertain nonlinear system control problem; virtual control value; Backstepping; Force; Neural networks; Robustness; Servomotors; Sliding mode control; Uncertainty; CMAC neural network; nonlinear system; sliding mode;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
Type :
conf
DOI :
10.1109/ICSPCC.2013.6663955
Filename :
6663955
Link To Document :
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