Online Identification and Alignment of MIMO Cross Directional Controlled Processes Using Second Order Statistics

Among the factors influencing the performance of multi-input multi-output (MIMO) systems such as paper machines, accurate spatial alignment of the actuators with their corresponding measurement points is a key issue in cross directional (CD) control. This mapping is a stochastic, non-linear and time-varying problem. Most current methods of alignment require a manual open-loop bump test. Several actuators are excited to perform the bump test, then the observed peaks are assigned to the excited actuators. This paper uses the second-order statistical technique of the blind source separation methods to make the transition from a manual, open-loop bump test to closed-loop adaptive online mapping. This procedure estimates the mixing matrix by spatial decorrelation of the noise and source signal. The mixing matrix is a function of input autocorrelation input and output cross-correlation. The main advantage of this method comes from the fact that we have direct access to the source signals and outputs. The method´s robustness in cases of spatially colored noise makes it applicable to the CD control of paper machines.