2509 System identification and control based on FE model and measured data

This study proposes a system modeling method based on FE model and measured data. The performance of the control system designed with the model obtained by this method is evaluated. Usually, a state space equation derived FE model is not enough accurate to achieve high control performance. On the other hand, when high-order MIMO model is identified by measured data, it's difficult to identify the precise model due to the complexity of the calculation. Therefore, this study introduces a method that tunes the state space equation derived FE model to fit the measured data. Simultaneous perturbation stochastic approximation (SPSA) is used as tuning algorithm. The vibration control experiment by using this tuned model is carried out and demonstrates the high vibration control performance.