A GA-optimized fuzzy PD+I controller for nonlinear systems

This paper presents a design and simulation study of a fuzzy PD+I controller optimized via a multi-objective genetic algorithm (MOGA). The fuzzy PD+I controller preserves the linear structure of the conventional PID controller but has self-tuned gains. The proportional, integral and derivative gains are nonlinear functions of their input signals, which have a certain adaptive capability in set-point tracking performance. The proposed design is then optimized by using the MOGA. It is tested with a couple of simulated nonlinear systems, which demonstrate that these optimized gains make the fuzzy PD+I controller robust, with a faster response time and less overshoot than its conventional and non-optimized counterparts