Hybrid Fuzzy Genetic Method to Evolve PID Analog Circuits

In this book chapter, we present a hybrid optimization strategy for tuning the gains of a Proportional-Integral-Derivative (PID) industrial controller analog circuit. This hybrid method consists of a multi-objective genetic algorithm with fuzzy aggregation, which incorporates the user reasoning and allows a better interpretation of results. Analog typical PID controllers are used whose component values are evolved in order to achieve acceptable performance specifications, by optimizing objectives regarding the PID input reference signal specifications such as overshoot, rise time and settling time. We evaluate the hybrid strategy in five control systems and different tuning strategies. The fuzzy-genetic approach obtained, on average, better results with a faster convergence, if compared to traditional approaches.