Semi-active Control of Structure Vibrations with MR Damper Using Fuzzy Control System (FLC) and Optimization through Genetic Algorithm (GA)

Abstract

Abstract. Magneto-Rheological (MR) damper is a new generation of dampers, filled up with a MR fluid. This fluid, when exposed to a magnetic field, will transform regularly from a slipper linear viscous fluid to a semi rigid state. In this article, semi-active control of structures equipped with MR damper is studied. For this purpose, fuzzy control theory is used to determine appropriate command voltage applied to MR damper; and genetic algorithm is used to optimize the fuzzy rules. Then, generated fuzzy rules database will improve fuzzy control system performance relative to experimental fuzzy rules database. Consequently, with applying an appropriate command voltage through an optimized fuzzy control system will decrease vibrations of the structures. The results show that, in the presence of optimized fuzzy rules through genetic algorithm, the amplitude of vibrations is decreased significantly.

Optimization of Fuzzy Control Systems Using the Genetic Algorithm

“…Для моделирования САР принято, что передаточная функция объекта управления соответствует инерционному звену первого порядка [6]: W(s) = K 0 /(T 0 s + 1) , где K 0 -коэффициент передачи; T 0 -постоянная времени. Приняты базовые (исходные) значения параметров объекта управления: K 0 = 0,25 кгс/см 2 /%, T 0 = 60 c. Исследование нечётких регуляторов проводилось при варьировании параметров объекта K 0 и T 0 на ±50 % от принятых значений [4][5][12][13][14].…”

Fuzzy logic control based on genetic algorithm for a multi-source excitations floating raft active vibration isolation system

“…In terms of the application of fuzzy control in vehicle suspension, 15,16 civil engineering structures, 17,18 flexible structures, 19 and other areas of engineering vibration and noise reduction, great achievements have been made. A Shehata et al 15 designed the fuzzy controllers for the vehicle suspension system, which improved the performance of the suspension system by changing the number and arrangement of rules and the scope of the domain, that is, the different types of fuzzy rules and membership functions were studied how to influence the performance of the active suspension system; X Dong et al 16 proposed an adaptive fuzzy logic control (FLC) based on a hybrid Taguchi genetic algorithm (GA) to overcome the limitations of conventional FLC strategies so as to suppress the vibration of the magneto-rheological (MR) suspension better; MR Elhami et al 17 used fuzzy control theory to determine appropriate command voltage applied to MR damper and GA to optimize the fuzzy rules, and experimental results showed that the amplitude of vibrations decreased significantly in the presence of optimized fuzzy rules through GA; ME Uz and MNS Hadi 18 proposed an optimal design strategy based on GAs for nonlinear hysteretic control devices, and the results obtained by fuzzy controller were compared with that gained from linear quadratic regulator (LQR) and H2/LQR; AHN Shirazi et al 19 investigated the active vibration control of a simply supported rectangular plate made from functionally graded materials (FGM) with FLC and compared the results obtained with the application of proportional-integral-derivative (PID) control, and results showed that FLC had better performance to dampen the vibration of the smart plate compared to PID control. Fuzzy control in these areas mainly focuses on single-input single-output control and rarely involves MIMO control.…”