An adaptive fuzzy controller for robot manipulators

Due to computational burden and dynamic uncertainty, the model based decoupling control approach is hard to be implemented in a multivariable robotic system. Here, a model-free model reference adaptive fuzzy sliding mode controller (MRAFSC) is proposed to control a five degree-of-freedom (DOF) robot. MRAFSC drives the system state variables to hit a user-defined sliding surface and then slide along it to approach a reference model. Consequent parameters of the fuzzy control can be initialized at zero, and then adjusted by using a novel online parameters tuning algorithm derived from the Lyapunov stability theory. A boundary layer function is introduced into the updating law to eliminate the chattering phenomenon which is inherent to the sliding mode control. The state errors converge into a specified error bound which depends on the boundary layer, parameter errors and modeling errors. The experimental results show that this novel controller has good control performance, stability and robustness.