An approximate-predictor approach to reduced-order models and controllers for distributed-parameter systems

Two reduced-order digital controllers for distributed parameter systems (DPS) are described. Reduced-order models approximate the optimal finite past predictor and error covariance for the full system to minimize an approximation to the Kullback-Leibler information distance (KLID). An LQG controller based on a reduced-order-system model is described. A reduced-order controller is found to minimize the KLID between the closed-loop system outputs with the full- and reduced-order controllers. Noncollocated control of a flexible beam is simulated.