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Sensitivity-constrained linear optimal control forced singular perturbation model reduction

A new approach to parameter desensitized optimal control is presented. This approach, which is based on forced singular perturbation model reduction, is different from the usual desensitization techiques in that it avoids realization problems - a well posed optimization problem always results, employs no sensitivity function generators, and requires no state vector augmentation.