Design On-Line Tunable Gain Artificial Nonlinear Controller

Abstract

One of the most important challenges in nonlinear, multi-input multi-output (MIMO) and time variant systems (e.g., robot manipulator) is designing a controller with acceptable performance. This paper focused on design a new artificial non linear controller with on line tunable gain applied in the robot manipulator. The sliding mode fuzzy controller (SMFC) was designed as 7 rules Mamdani’s inference system because it has one input as sliding function and one output as fuzzy sliding function which the integral part was added to the sliding function in the presence of uncertainties and external disturbance to reduce the limitations. Sliding mode controller (SMC) has two most important challenges in uncertain systems: chattering phenomenon and nonlinear dynamic equivalent part. Applying the sliding mode methodology to Mamdani ’s fuzzy logic controller with minimum rules was the first goal that caused the stability development. Second target focused on the elimination of chattering phenomenon with regard to the variety of uncertainty and external disturbance in fuzzy sliding mode controller by on-line optimization the tunable gain.