Saturday 25th of November 2017
 

Sliding Mode ANFIS-Based MIMO Fuzzy Neural Network Control for Robotic Systems


Yi-Jen Mon

This paper develops a design methodology of sliding mode ANFIS-Based multi-inputs multi-outputs (MIMO) fuzzy neural network (AMFNN) control for robotic systems. This control system consists of a sliding mode (SM) controller and an AMFNN controller. The SM controller is used to deal with uncertain parts of system dynamics and external disturbances and the AMFNN controller is served as a controller approaching the ideal controller of SM controller to stabilize the system. The ANFIS-Based laws of the AMFNN parameters are derived so that the stability and convergence of the systemís parameters of AMFNN can be guaranteed. The simulation results reveal that the better performances are possessed by the proposed AMFNN control compared with the adaptive fuzzy neural network (AFNN) control and state feedback control.

Keywords: ANFIS, multi-inputs multi-outputs (MIMO), fuzzy neural network, Robotic system, Sliding mode control.

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ABOUT THE AUTHOR

Yi-Jen Mon
Associated Prof.


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