Reduced Order Controllers for Spatially Distributed Systems via Proper Orthogonal Decomposition

A method for reducing controllers for systems described by partial di erential equations (PDEs) is presented. This approach di ers from an often used method of reducing the model and then designing the controller. The controller reduction is accomplished by projection of a large scale nite element approximation of the PDE controller onto low order bases that are computed using the proper orthogonal decomposition (POD). Two methods for constructing input collections for POD, and hence low order bases, are discussed and computational results are included. The rst uses the method of snapshots found in POD literature. The second is a new idea that uses an integral representation of the feedback control law. Speci cally, the kernels, or functional gains, are used as data for POD. A low order controller derived by applying the POD process to functional gains avoids subjective criteria associated with implementing a time snapshot approach and performs favorably.