Soft constraints in identification of distributed parameters

In this article, we introduce an idea of using soft constraint to improve effectiveness of existing optimization methods for identifying unknown parameter zones for distributed parameter identification problems. The constraint is put on the projected size of each parameter zone. But the constraint is only softly imposed due to uncertainty consideration. Two identification procedures based on such a constrained optimization idea are described. Results on three examples are presented to illustrate the advantages of this new approach.