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

Smart base-isolation strategies are being widely investigated as a way to reduce structural damage caused by severe loads. This study uses a friction pendulum system (FPS) as the isolator and a magnetorheological (MR) damper as the supplemental damping device 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. The findings show that the proposed method can find optimal fuzzy rules and that the NSGA-II-optimized FLC outperformed a passive control strategy, a conventional semiactive control algorithm and a human-designed FLC.

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