Home Articles List Article Information
JES. Journal of Engineering Sciences
Journal Archive
Volume Volume 53 (2025)
Volume Volume 52 (2024)
Volume Volume 51 (2023)
Volume Volume 50 (2022)
Volume Volume 49 (2021)
Volume Volume 48 (2020)
Volume Volume 47 (2019)
Volume Volume 46 (2018)
Volume Volume 45 (2017)
Volume Volume 44 (2016)
Volume Volume 43 (2015)
Volume Volume 42 (2014)
Volume Volume 41 (2013)
Volume Volume 40 (2012)
Volume Volume 39 (2011)
Volume Volume 38 (2010)
Volume Volume 37 (2009)
Volume Volume 36 (2008)
Volume Volume 35 (2007)
Volume Volume 34 (2006)
Sharkawy, A., Salman, S. (2012). AN ADAPTIVE FUZZY SLIDING MODE CONTROL SCHEME FOR ROBOTIC SYSTEMS. JES. Journal of Engineering Sciences, 40(No 1), 173-189. doi: 10.21608/jesaun.2012.112724
Abdel Badie Sharkawy; Shaaban A. Salman. "AN ADAPTIVE FUZZY SLIDING MODE CONTROL SCHEME FOR ROBOTIC SYSTEMS". JES. Journal of Engineering Sciences, 40, No 1, 2012, 173-189. doi: 10.21608/jesaun.2012.112724
Sharkawy, A., Salman, S. (2012). 'AN ADAPTIVE FUZZY SLIDING MODE CONTROL SCHEME FOR ROBOTIC SYSTEMS', JES. Journal of Engineering Sciences, 40(No 1), pp. 173-189. doi: 10.21608/jesaun.2012.112724
Sharkawy, A., Salman, S. AN ADAPTIVE FUZZY SLIDING MODE CONTROL SCHEME FOR ROBOTIC SYSTEMS. JES. Journal of Engineering Sciences, 2012; 40(No 1): 173-189. doi: 10.21608/jesaun.2012.112724

AN ADAPTIVE FUZZY SLIDING MODE CONTROL SCHEME FOR ROBOTIC SYSTEMS

Article 10, Volume 40, No 1, January and February 2012, Page 173-189  XML PDF (251.87 K)
Document Type: Research Paper
DOI: 10.21608/jesaun.2012.112724
View on SCiNiTO View on SCiNiTO
Authors
Abdel Badie Sharkawy email 1; Shaaban A. Salman2
1Associate Professor, Mechanical Engineering Department, Faculty of Engineering, Assiut University, 71516, EGYPT
2Mechanical Engineering Department, Faculty of Engineering, Assiut University, 71516 Assiut, Egypt
Abstract
In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a model-free fuzzy sliding mode control. The equivalent controller has been replaced by a fuzzy system and the uncertainties are estimated on-line. The approach of the AFSMC has the learning ability to generate the fuzzy control actions and adaptively compensates for the uncertainties. Despite the high nonlinearity and coupling effects, the control input of the proposed control algorithm has been decoupled leading to a simplified control mechanism for robotic systems. Simulations have been carried out on a two link planar robot. Results show the effectiveness of the proposed control system.
Keywords
Sliding mode control (SMC); Adaptive fuzzy sliding mode control (AFSMC); Fuzzy logic control (FLC); Adaptive laws; Robotic control
Main Subjects
Mechanical, Power, Production, Design and Mechatronics Engineering.
Statistics
Article View: 113
PDF Download: 237