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L.-C. Hung and H.-Y. Chung, “Decoupled Sliding-Mode with Fuzzy-Neural Network Controller for Nonlinear Systems,” International Journal of Approximate Reasoning, Vol. 46, No. 1, 2007, pp. 74-97. doi:10.1016/j.ijar.2006.08.002

has been cited by the following article:

• TITLE: An Adaptive Fuzzy Sliding Mode Control Scheme for Robotic Systems

  AUTHORS: Abdel Badie Sharkawy, Shaaban Ali Salman

  KEYWORDS: Sliding Mode Control (SMC), Adaptive Fuzzy Sliding Mode Control (AFSMC), Fuzzy Logic Control (FLC), Adaptive Laws, Robotic Control.

  JOURNAL NAME: Intelligent Control and Automation, Vol.2 No.4, November 2, 2011

  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 substituted for 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.