Assessing fuzzy and neural approaches for a PID controller using universal model

Despite the popularity, the tuning aspect of PID controllers is a challenge for researches and plant operators. Various control design methodologies have been proposed in the literature such as auto-tuning, self-tuning and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning parameters to be selected. In this paper, the design of a PID controller, based on the universal model of the plant, is derived. The design characteristic has only one parameter to be tuned. This is a good idea from the viewpoint of plant operators. Fuzzy and neural approaches are used for designing and assessing the efficiency of the PID control in nonlinear plants.