Home /Research /Parallel robot with fuzzy neural network sliding mode control
LEARNING

Parallel robot with fuzzy neural network sliding mode control

Jiangmin Xu, Qi Wang, Qing Lin

Year
2018
Citations
26
Access
Open access

Abstract

With the advancement in research on parallel robots, control theory is increasingly applied in the field of robotics. Owing to its robustness, sliding mode variable structure control is extensively used in parallel robots. This article presents an adaptive sliding mode control method for nonlinear systems. A parallel robot control model with adaptive fuzzy sliding mode control was designed based on a fuzzy neural network control theory, and simulation results demonstrate its effectiveness of the method.

Keywords

Sliding mode controlVariable structure controlRobustness (evolution)Artificial neural networkControl theory (sociology)RobotControl engineeringComputer scienceFuzzy control systemFuzzy logic

Related papers

Browse all LEARNING papers