Input–parameter–state estimation of limited information wind‐excited systems using a sequential Kalman filter
Marios Impraimakis, Andrew W. Smyth
Abstract
The estimation of the dynamic states, the parameters, and the input of systems subjected to wind loading is examined herein using a sequential Kalman filter. The procedure considers two Kalman filters in order to estimate initially the dynamic states and subsequently the system parameters along with the input, in an online fashion. The approach results in an accurate convergence as demonstrated by two linear systems with limited information and two nonlinear applications.
Topics & Concepts
Kalman filterExtended Kalman filterFast Kalman filterControl theory (sociology)Convergence (economics)Invariant extended Kalman filterComputer scienceNonlinear systemAlpha beta filterEstimation theoryState (computer science)Moving horizon estimationEnsemble Kalman filterAlgorithmMathematicsArtificial intelligencePhysicsControl (management)Economic growthEconomicsQuantum mechanicsStructural Health Monitoring TechniquesWind and Air Flow StudiesProbabilistic and Robust Engineering Design