  We develop an algorithm based on the nudging data assimilation scheme for the
concurrent (on-the-fly) estimation of scalar parameters for a system of
evolutionary dissipative partial differential equations in which the state is
partially observed. The algorithm takes advantage of the error that results
from nudging a system with incorrect parameters with data from the true system.
The intuitive nature of the algorithm makes its extension to several different
systems immediate, and it allows for recovery of multiple parameters
simultaneously. We test the method on the Kuramoto-Sivashinsky equation in one
dimension and demonstrate its efficacy in this context.
