Published Paper Details:

Based on traditional PID control and nonlinear components, this research provides an optimum fuzzy proportional-integral-derivative (PID) controller architecture. Because of the similarity between fuzzy logic controllers (FLCs) and traditional PID controllers, a typical PID controller design may be quickly turned into an equivalent FLC by defining the controller's working ranges. The suggested nonlinear factors can be used to fine-tune the nonlinearity of the membership functions (MFs) that are dispersed throughout the operational ranges. In this approach, a fuzzy PID controller with fewer parameters may be built and optimized using the genetic algorithm (GA). Furthermore, the aforementioned corresponding FLC can operate as one member in the initial GA population, considerably improving GA efficiency. The simulation results show that this strategy is feasible. This resulted in an ideal fuzzy PID controller design with only eight parameters and a compact controller layout, as well as a more systematic optimal fuzzy PID controller design.