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Adaptive pole placement control of paper machines with singular pencil models

The problem of pole placement for linear stochastic systems is considered. The system, represented in state space form, is formulated into a singular pencilsystem model whose internal variables and parameters are estimated using an ordinary Kalman filter. The estimated internal variables and parameters are then used in the state feedback controller to place the poles of the closed loop system onto desired locations.