An adaptive fuzzy sliding mode control for angle tracking of human musculoskeletal arm model. (November 2018)

• Record Type: Journal Article
• Authors: Xiuxiang, Chen; Ting, Wang; Yongkun, Zhao; Wen, Qin; Xinghua, Zhang
• Is Part Of: Computers & electrical engineering. Volume 72(2018)
• Page Start: 214
• Page End: 223
• Publication Date: 2018-11
• Subjects: Human musculoskeletal model -- Gravity compensation -- Sliding mode control -- Angle tracking; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.09.013
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: The paper studies the angle tracking control of the elbow joint and the end-point of the human musculoskeletal arm model. It uses a Hill-type planar model with six muscles and two links. During the motion, the gravity compensation is emphasized since it has significant influence on actual anthropomorphic arm system. An adaptive fuzzy sliding mode control method is proposed and applied to make the elbow joint and the end point of the human musculoskeletal arm model track certain angles. Through the adaptive fuzzy system, it may realize the adaptive approximation of switching scales of sliding mode controller so as to avoid chattering. Numerical simulations are performed in order to verify the proposed control method. Results show that accurate angle tracking control may well be accomplished by proposed sliding mode controller.