A multi‐time‐delay compensation controller using a Takagi–Sugeno fuzzy neural network method for high‐rise buildings with an active mass damper/driver system

2019 ◽  
Vol 28 (13) ◽  
Author(s):  
Zuo‐Hua Li ◽  
Chao‐Jun Chen ◽  
Jun Teng
Keyword(s):  
Fuzzy Neural Network ◽  
Delay Compensation ◽  
Active Mass ◽  
High Rise ◽  
Mass Damper ◽  
Network Method ◽  
Active Mass Damper ◽  
Fuzzy Neural ◽  
Time Delay Compensation ◽  
Takagi Sugeno

scholarly journals Seismic Resistance and Parametric Study of Building under Control of Impulsive Semi-Active Mass Damper

2021 ◽  
Vol 11 (6) ◽  
pp. 2468
Author(s):  
Ming-Hsiang Shih ◽  
Wen-Pei Sung
Keyword(s):  
Frequency Ratio ◽  
Efficiency Index ◽  
Reduction Ratio ◽  
Seismic Resistance ◽  
Control Effect ◽  
Active Mass ◽  
High Rise ◽  
Mass Damper ◽  
Active Mass Damper ◽  
External Forces

When high-rise buildings are shaken due to external forces, the facilities of the building can be damaged. A Tuned Mass Damper (TMD) can resolve this issue, but the seismic resistance of TMD is exhausted due to the detuning effect. The Impulsive Semi-Active Mass Damper (ISAMD) is proposed with fast coupling and decoupling at the active joint between the mass and structure to overcome the detuning effect. The seismic proof effects of a high-rise building with TMD and ISAMD were compared. The numerical analysis results indicate that: (1) the reduction ratio of the maximum roof displacement response and the mean square root of the displacement reduction ratio of the building with the ISAMD were higher than 30% and 60%, respectively; (2) the sensitivity of the efficiency index to the frequency ratio of the ISAMD was very low, and detuning did not occur in the building with the ISAMD; (3) to achieve stable seismic resistance of the ISAMD, its frequency ratio should be between 2 and 4; (4) the amount of displacement of the control mass block of the ISAMD can be reduced by enhancing the stiffness of the auxiliary spring of the ISAMD; and (5) the proposed ISAMD has a stable control effect, regardless of the earthquake distance.

Fuzzy neural network control algorithm for asymmetric building structure with active tuned mass damper

2020 ◽  
Vol 26 (21-22) ◽  
pp. 2037-2049
Author(s):  
Xiao Yan ◽  
Zhao-Dong Xu ◽  
Qing-Xuan Shi
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Neural Network ◽  
Linear Quadratic Regulator ◽  
Tuned Mass Damper ◽  
Linear Quadratic ◽  
Mass Damper ◽  
Fuzzy Neural ◽  
Neural Network Algorithm ◽  
Damper Control

Asymmetric structures experience torsional effects when subjected to seismic excitation. The resulting rotation will further aggravate the damage of the structure. A mathematical model is developed to study the translation and rotation response of the structure during seismic excitation. The motion equations of the structures which cover the translation and rotation are obtained by the theoretical derivations and calculations. Through the simulated computation, the translation and rotation response of the structure with the uncontrolled system, the tuned mass damper control system, and active tuned mass damper control system using linear quadratic regulator algorithm are compared to verify the effectiveness of the proposed active control system. In addition, the linear quadratic regulator and fuzzy neural network algorithm are used to the active tuned mass damper control system as a contrast group to study the response of the structure with different active control method. It can be concluded that the structure response has a significant reduction by using active tuned mass damper control system. Furthermore, it can be also found that fuzzy neural network algorithm can replace the linear quadratic regulator algorithm in an active control system. Because fuzzy neural network algorithm can control the process on an uncertain mathematical model, it has more potential in practical applications than the linear quadratic regulator control method.

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