Design of a genetic-fuzzy inverse controller for a slider crank mechanism

Many research efforts have been made to develop the slider-crank mechanism. Design of a genetic-fuzzy inverse controller for a slider crank mechanism with the piston cylinder drive is studied. This mechanism converts the translating motion into rotating motion. In this approach, the computed torque is implemented to obtain high speed and precise position tracking also; compensation of unknown uncertainties and disturbances is achieved using Mamdani-type fuzzy controller. The fuzzy controller parameters are optimized using a genetic algorithm. Computer simulations are carried out, and the results are presented to illustrate high tracking capability and effectiveness of the proposed control approach.