基于智能算法的高层建筑非线性地震反应的MR阻尼器半主动控制

研究了第三阶段结构振动控制的Benchmark问题;设计了基于模糊神经网络的控制器模型;采用磁流变(MR)阻尼器作为控制装置,对一座20层Benchmark建筑结构进行了非线性地震反应的数值仿真分析。首先,通过神经网络对足尺MR阻尼器进行了动力特性的辨识;其次,在设计模糊神经网络控制器时,提出了分区控制的设计思路。将智能控制器半主动控制下的仿真结果与样本LQG控制进行了对比分析。结果表明:提出的智能控制器能有效抑制高层建筑结构的非线性地震反应;与样本LQG控制相比,由于智能控制器的内在鲁棒性和对结构非线性反应控制的稳定性,在非线性结构的振动控制中有很大的应用潜力。

INTELLIGENT ALGORITHM BASED SEMI-ACTIVE CONTROL OF MR DAMPER OF NONLINEAR SEISMIC RESPONSE FOR HIGH-RISE BUILDINGS

A third generation Benchmark problem on structural control is investigated and a controller based on fuzzy neural network is designed. Numerical simulation is carried out for analyzing the nonlinear seismic responses of the controlled 20-story Benchmark building with MR (Magneto-Rheological) damper. Firstly, a neural network is employed to identify the dynamic characteristics of the full-scale MR damper. In designing a fuzzy neural network controller, a new idea based on zoning control is proposed. The simulation results are compared with those of LQG sample-control systems. The analytical results show that the developed semi-active strategy has good performance, and can reduce the nonlinear seismic response of high-rise building and the damages in the building structures caused by strong earthquakes. Although the control efficiency of the intelligent controller is a little less than that of LQG-sample active controller on some values of evaluation criteria, the intrinsic robustness of controller can prove that the intelligent controller has a good potential in the control of nonlinear vibrations of structures.