Sensitivity-based self-learning fuzzy logic controller as a PLC super block

In this article, implementation of a self-learning fuzzy logic controller (SLFLC) in a form of PLC super block is described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the PLC super block has been tested by experiment in the position control loop of an electronically commutated servo system in the presence of a gravity-dependent shaft load. The experimental results have proved that the SLFLC implemented in PLC provides desired closed-loop behavior.