Particle Swarm Optimization-Based Parameter Identification Method for Euler-Bernoulli Beam

The Euler-Bernoulli beam is a typical spatio-temporal coupled flexible system. Due to the uncertain parameters, it is difficult for most models to accurately describe the dynamic characteristics of Euler-Bernoulli beam. To overcome above problem, a particle swarm optimization-based parameter identification method is proposed for a class of Euler-Bernoulli beam systems in this paper. First, by improving the Karhunen-Loève method, the original infinite-dimensional partial differential equation (PDE) model is transformed into the finite-dimensional ordinary differential equation (ODE) model. Second, the multi-parameters are accurately estimated by applying the particle swarm optimization method. Third, the proposed methodology for model reduction and parameter identification is validated and demonstrated to be excellent through a comparison of three simulation results.