Parameter identification and vibration suppression for Flexible Aircraft Wings based on Support Vector Machine

This study investigates the control challenges of flexible aircraft wings through parameter identification. The Disturbances affecting flexible aircraft wings are commonly assumed to be random, making it difficult to satisfy the necessary statistical assumptions. Thus, we propose a parameter identification approach against specific parameters of aircraft wings based on a support vector machine (SVM) to rddress this situation. To suppress the elastic deformation of the flexible aircraft wings, a boundary control scheme based on a radial basis function (RBF) neural network is proposed based on the identification results. Finally, two simulation examples are provided to validate the effectiveness of the parameter identification method and the boundary controller respectively.