Monday 19th of February 2018

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.

Download Full-Text


Yi-Jen Mon
Associated Prof.

IJCSI Published Papers Indexed By:





IJCSI is a refereed open access international journal for scientific papers dealing in all areas of computer science research...

Learn more »
Join Us

Read the most frequently asked questions about IJCSI.

Frequently Asked Questions (FAQs) »
Get in touch

Phone: +230 911 5482

More contact details »