We can solve your most challenging system identification problems.
We can directly estimate a state-space model of your system/plant by using the subspace identification method. This model can be used for control system design or for the design of an estimator such as the Kalman filter or the moving horizon estimator.
We can directly estimate a transfer function of your system/plant by using the prediction error method and output error method. We can provide confidence intervals and a full statistical analysis of the estimated model prediction performance.