“Steady-State Error Reduction with Fuzzy Gain Scheduling Integrator”
Ali Kazemy1 , Seyed Amin Hosseini1 and Mohammad Farrokhi1,2
Abstract — In this paper, first, the dynamic equations of a submarine periscope will be extracted and verified with real data. These data are acquired from an experimental setup. Then, using a neural network, an intelligent control method will be developed to control the periscope model. For steady state error reduction of the main controller a Fuzzy Gain Scheduling (FGS) integrator scheme has been used. This integrating controller is parallel to the main controller. The main issue is to adjust the integrator gain using fuzzy logic to decrease the steadystate error, while maintaining stability of the closed-loop system. Fuzzy IF-THEN rules are used to adjust the gain of the integrator based on the tracking error and its derivative. Simulation results on the plant model indicate good performance of the proposed method.