Robot Control by Using Intelligent Systems Considering Complete Constraints

In this paper, a multivariable control of a two-link robot is performed by fuzzy-sliding mode control. Robots on the one hand have complex dynamics due to nonlinearity, uncertainty and indeterminacy resulting from friction and other factors. The uncertainty and nonlinearity of the governing equations more and more necessitates the use of these two types of controllers in spite of a two-link and multivariable dynamic system. In this paper simulation, a fuzzy system is used in two parts. In the first part, a fuzzy system is used to approximate the uncertainty of the robot arm dynamic model in the control law and in the second part the nonlinear term of the signal function is replaced by an adaptive neuro-fuzzy controller to produce appropriate k s and to track the output properly. The comparison of simulation results suggests that the intelligent method based on the proposed adaptive neuro-fuzzy control has better performance in tracking reference signal with slight tracking error and higher accuracy compared to sliding mode method.