Robots extension control using fuzzy smoothing

The paper presents a new control method for the robot extension control, using the Extenics concepts and Extension Theory techniques. The controller uses the Dependent Function to measure the degree of compatibility of the process variable and then takes the appropriate action to force the system into convergence around a desired set point. The output of the Dependent Function classifies the process variable value into one of four categories, concurrent with the nested intervals used in Extenics, which are then equated to fuzzy inputs sets of a linguistic variable for a simple fuzzy controller. This acts as a fuzzy smoothing of the controller output. The rationality and validity of the proposed model are demonstrated through simulation in the Matlab/Simulink environment. The results show that the proposed new controller architecture obtains remarkable results, while having the advantage of increased simplicity in design and setting of parameters. Throughout the paper, opportunities for further improvement and research are highlighted and discussed.