Vibration Suppression of a High-Rise Building With Adaptive Iterative Learning Control

IEEE transactions on neural networks and learning systems(2023)

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Abstract
This article considers the design of an adaptive iterative learning controller for high-rise buildings with active mass dampers (AMDs). High-rise buildings in this article are seen as distributed parameter systems, in which the characteristics of every point in buildings should be considered. Two partial differential equations (PDEs) and several ordinary differential equations are used to describe the model of buildings. To achieve the control target that is to suppress the vibration induced by high winds, an adaptive iterative learning controller is proposed for the flexible building system with boundary disturbance. The convergency of the adaptive iterative learning control (AILC) approach is proven by serious theory analysis. In simulations and experiments, this article uses both the analysis of figures and quantitative analysis (root-mean-square values) to illustrate the efficiency of the AILC scheme.
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Key words
Buildings,Mathematical models,Vibrations,Shock absorbers,Adaptive systems,Adaptation models,Iterative learning control,Active mass damper (AMD),adaptive iterative learning control (AILC),distributed parameter system (DPS),high-rise buildings,vibration control
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