Fuzzy Control of Base-Isolation System Using Multi-Objective Genetic Algorithm

In this study, a friction pendulum system (FPS) and a magnetorheological (MR) damper are employed as the isolator and supplemental damping device, respectively, of a smart base-isolation system. Neuro-fuzzy models are used to represent dynamic behavior of the MR damper and FPS. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme that uses a nondominated multi-objective genetic algorithm (NSGA-II) is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate the effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base-isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the NSGA-II-optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semiactive control algorithm.