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Semiactive conceptual fuzzy control of magnetorheological dampers in an irregular base‐isolated benchmark building optimized by multi‐objective genetic algorithm
Author(s) -
Mehrkian Behnam,
Bahar Arash,
Chaibakhsh Ali
Publication year - 2019
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2302
Subject(s) - benchmark (surveying) , damper , magnetorheological fluid , base isolation , genetic algorithm , engineering , fuzzy logic , base (topology) , controller (irrigation) , nonlinear system , control theory (sociology) , vibration control , structural engineering , vibration , control (management) , computer science , artificial intelligence , mathematics , telecommunications , agronomy , physics , frame (networking) , quantum mechanics , biology , geography , mathematical analysis , geodesy , machine learning
Summary Seismic base isolations are well‐established passive control systems, used for reducing structural responses and preventing interior sensitive equipment and nonstructural elements from damaging. However, in a base‐isolated structure under near‐fault earthquakes, isolated layers sustain large displacements that might not be allowable. Further, any passive limitation in these displacements amplifies vibration transmissions to the superstructure. Smart hybrid base isolations using magnetorheological (MR) dampers, as well‐known semiactive devices, can overcome this problem by smart dampening. Nonetheless, highly nonlinear hysteretic behavior of MR dampers is one of the challenges for model‐based control algorithms. In this study, a smart multi‐objective fuzzy‐genetic control for dampening the vibrations of structures in an irregular base‐isolated benchmark building subjected to different earthquake scenarios is presented. The control aims, on one hand, to conserve (or even improve) top isolation characteristics in unique restraining of floor accelerations and drifts and, on the other hand, to mitigate large base displacements under near‐fault earthquakes using MR dampers simultaneously. Unlike many smart controls with a black‐box performance, the proposed fuzzy core is constructed conceptually employing control expertise with respect to the plant. To achieve control objectives, a conceptual innovative feedback is proposed for fuzzy decision making. To optimize this human‐designed controller, a multi‐objective genetic algorithm is applied. For evaluation, a three‐dimensional nonlinear irregular base‐isolated benchmark building planned by the American Society of Civil Engineers is employed. In comparison with classical and smart controls, the results demonstrate that despite having the smallest structure with fast performance, the proposed control effectively diminishes conflicting responses and has better performance than other controls.