Evolutionary Design of Backstepping Artificial Sliding Mode Based Position Algorithm: Applied to Robot Manipulator

This paper expands a fuzzy sliding mode based position controller whose sliding function is on-line tunedby backstepping methodology. The main goal is to guarantee acceptable position trajectories trackingbetween the robot manipulator end-effector and the input desired position. The fuzzy controller inproposed fuzzy sliding mode controller is based on Mamdani’s fuzzy inference system (FIS) and it has oneinput and one output. The input represents the function between sliding function, error and the rate oferror. The second input is the angle formed by the straight line defined with the orientation of the robot,and the straight line that connects the robot with the reference cart. The outputs represent angularposition, velocity and acceleration commands, respectively. The backstepping methodology is on-line tunethe sliding function based on self tuning methodology. The performance of the backstepping on-line tunefuzzy sliding mode controller (TBsFSMC) is validated through comparison with previously developed robotmanipulator position controller based on adaptive fuzzy sliding mode control theory (AFSMC). Simulationresults signify good performance of position tracking in presence of uncertainty and external disturbance.