Optimal Semi-active Structural Control with a Wavelet-Based Cuckoo-Search Fuzzy Logic Controller

Abstract

An adjustable cuckoo-search wavelet-based fuzzy logic controller (ACSWBFLC) is introduced to mitigate structural responses during seismic motion by using magnetorheological (MR) dampers. The ACSWBFLC incorporates four algorithms: discrete wavelet transform (DWT), fuzzy logic controller (FLC), modified Bouc–Wen model and geometrical nonlinearity algorithm. DWT is applied to acquire the local energy distribution of seismic excitation over the frequency bands. These online data are transmitted to FLC to operate MR damper intelligently based on online excitation frequency. Furthermore, modified Bouc–Wen phenomenological algorithm was utilized to generate the nonlinear behavior of the MR dampers. A wavelet low-pass filter is employed to prevent the stabilization of coefficients and minimize the computational burden. Moreover, geometrical nonlinearities were considered to design a more robust controller. Furthermore, a novel evolutionary algorithm of cuckoo search was used to optimize the placement and the number of MR dampers and sensors in the sense of minimum resultant vibration magnitude. Numerical efforts were considered to validate the efficiency of the proposed FLC. From a designer’s point of view, the proposed ACSWBFLC controller can determine the optimal solutions during a reasonable number of iterations. Finally, numerical examples are utilized to demonstrate the efficiency of ACSWBFLC under several far- and near-fault seismic excitations. The results indicate that ACSWBFLC attenuates the excessive responses of the structural building in real time more efficiently than traditional FLC controllers by using appropriate control force.