Fuzzy-sliding mode control of a polishing robot based on genetic algorithm

This paper proposes a fuzzy-sliding mode control which is designed by a sel f tuning fuzzy inference method based on a genetic algorithm, Using the met hod, the number of inference rules and the shape of the membership function s of the proposed fuzzy-sliding muds control are optimized without the aid of an expert in robotics, The fuzzy outputs of the consequent part are upda ted by the gradient descent method. It is further guaranteed that the selec ted solution becomes the global optimal solution by optimizing Akaike's inf ormation criterion expressing the quality of the inference rules, In order to evaluate the learning performance of the proposed fuzzy-sliding mode con trol based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fu zzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-slidin g mode control which is selected through trial error by an expert. Therefor e, a designer who does not have expert knowledge of robot systems can desig n the fuzzy sliding mode controller using the proposed self tuning fuzzy in ference method based on the genetic algorithm.