Simulation and Modelling of Smart Beams with Robust Control Subjected to Wind Induced Vibration

Abstract

This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a finite element formulation with embedded control. The control aims at vibration suppression of the structure subjected to external disturbances, like wind and noise, under the presence of model inaccuracies, using the available measurements and controls. A smart structure under dynamic loads is analysed and comparison between results for beam with and without control is made. The numerical results show that the control strategy is very effective and suppresses the vibrations of the structure.

Vibration suppression in smart structures using fractional order PD controllers

“…For this particular reason, the fuzzy logic control algorithms have been highly successful in vibration control of flexible structures [7,8,9]. Apart from these, robust control strategies are also an adequate choice due to their intrinsic ability of ensuring a robust closed loop behavior, despite modeling uncertainties and estimation errors [10].…”

On the Torsional–Translational Response of Wind Turbine Structures

“…e.g. [13][14]). Advanced mathematical models for the analysis of the structural response of horizontal axis wind turbines with flexible tower and blades were developed by Kessentini et al [15], where the eigenvalue problem was treated both analytically and numerically by applying the differential quadrature method.…”

Tuning Method of Fractional Order Controllers for Vibration Suppression in Smart Structures

“…In this paper, the vibration suppression of such a smart structure equipped with PZT patches is discussed, however the results may be further extended since the wings of an aircraft may be regarded as cantilever structures [8] similar to the smart beam considered as a case study. For smart beams, various control strategies have been proposed for the suppression of resonance vibrations, such as LQR (linear quadratic regulator), LQG (linear quadratic Gaussian) controller [9], robust H ∞ control algorithms [10], fuzzy logic controllers [11], position feedback control, strain rate feedback control and lead compensation [12]. Such controllers are preferred due to the robust behavior against unknown disturbances, loads and modeling uncertainties.…”