Wavelet Network for Semi-Active Control

TL;DR: A wavelet neurocontroller capable of selfadaptation and self-organization for uncertain systems controlled with semiactive devices that are ideal candidates for control of large-scale civil structures is defined in this paper.

Abstract: This paper proposes a wavelet neurocontroller capable of self-adaptation and self-organization for uncertain systems controlled with semiactive devices that are ideal candidates for control of large-scale civil structures. A condition on the sliding surface for cantilever-like structures is defined. The issue of applicability of the control solution to large-scale civil structures is made the central theme throughout the text, as this topic has not been extensively discussed in the literature. Stability and convergence of the proposed neurocontroller are assessed through various numerical simulations for harmonic, earthquake, and wind excitations. The simulations consist of semiactive dampers installed as a replacement for the current viscous damping system in an existing structure. The controller uses only localized measurements. Results show that the controller is stable for both active and semiactive control using limited measurements and that it is capable of outperforming passive control strategies for earthquake and wind loads. In the case of wind loads, the neurocontroller is found to also outperform a linear quadratic regulator (LQR) controller designed using full knowledge of the states and system dynamics.