Design of new fuzzy sliding mode controller based on parallel distributed compensation controller and using the scalar function
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- 作者：Lotfi Chaouech ; chaouech.lotfi@yahoo.fr" class="auth_mail" title="E-mail the corresponding author ; Moê ; z Soltani ; Slim Dhahri ; Abdelkader Chaari
- 关键词：Takagi&ndash ; Sugeno fuzzy model ; Sliding mode control ; Parallel distributed compensation ; Linear quadratic regulator ; Scalar sign function
- 刊名：Mathematics and Computers in Simulation
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：132
- 期：Complete
- 页码：277-288
- 全文大小：555 K
文摘
This paper presents a new design of fuzzy sliding mode controller based on parallel distributed compensation and using a scalar 
function. The proposed fuzzy sliding mode controller (FSMC) uses the parallel distributed compensation (PDC) scheme to design the state feedback control law. The controller gains are determined in offline mode via linear quadratic regulator technique. Moreover, the fuzzy sliding surface of the system is designed using stable eigenvectors and the scalar function in order to overcome the discontinuous switching. This later is obtained by a function of the standard FSMC. The advantages of the proposed design are a minimum energy control effort, faster response and zero steady-state error. Finally, the validity of the proposed design strategy is demonstrated through the simulation of a flexible joint robot.
function. The proposed fuzzy sliding mode controller (FSMC) uses the parallel distributed compensation (PDC) scheme to design the state feedback control law. The controller gains are determined in offline mode via linear quadratic regulator technique. Moreover, the fuzzy sliding surface of the system is designed using stable eigenvectors and the scalar function in order to overcome the discontinuous switching. This later is obtained by a function of the standard FSMC. The advantages of the proposed design are a minimum energy control effort, faster response and zero steady-state error. Finally, the validity of the proposed design strategy is demonstrated through the simulation of a flexible joint robot.