Hybrid Fuzzy Controller Design for Position Control System

Abstract

A linear control system can be controlled by using the conventional controller after formulating a mathematical model of the system and finding its transfer function. The fuzzy logic controller enables the representation of human information pertaining to the system's control, manipulation, and execution. The developer of a controller must establish the rules, and the information may come from the human controller or from an understanding of the plant dynamics. The expansion in the rules leads the fuzzy controller to take efficient decisions and to be very strong for controlling the plant, besides the ability to control the nonlinearity that occurs in the plant. In this paper, the transfer function and response to a unit-step input of a closed-loop position control system were derived. The response of the system was improved by the design and simulation of a PD controller. Then, the formulation and construction of four fuzzy controllers gradually increase in the rule base 9, 25, 47, and 81. Finally, design and simulate a hybrid fuzzy controller. The system was simulated using MATLAB Simulink, examining a range of factors such as the rise, settling time, and overshoot. The implementation of a hybrid-fuzzy controller provides the benefits of the fuzzy controller and PD controller. This means that the hybrid fuzzy has a better transient response than the uncontrolled system, a system with PD controller, and a fuzzy controller.