A sensitivity-based self-learning fuzzy logic controller as a solution for a backlash problem in a servo system

In this paper, a self-learning fuzzy logic controller (SLFLC) is described whose learning algorithm utilizes a second-order reference model and a sensitivity model. The effectiveness of the proposed controller has been tested in the position control loop of a DC servomotor system affected by a backlash nonlinearity. The simulation results have proved that the SLFLC provides a desired closed-loop behavior and also significantly reduces a steady-state position error caused due to the presence of a backlash.