Abstract: The paper describes the use of subspace based
identification methods for auto tuning of a state space control system.
The plant is an unstable but self balancing transport robot. Because
of the unstable character of the process it has to be identified
from closed loop input-output data. Based on the identified model
a state space controller combined with an observer is calculated. The
subspace identification algorithm and the controller design procedure
is combined to a auto tuning method. The capability of the approach
was verified in a simulation experiments under different process
conditions.
Abstract: Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.