On estimation algorithms for ordinary differential equations

This article addresses the problem of estimating the parameters of a system of ordinary differential equations given data derived from noisy observations on the state variables. This problem is important in a range of applications in areas such as adaptive, real time control. There are two main classes of method for attacking this problem, and their equivalence and effectiveness (consistency) are discussed. Recent rate of convergence results for the major implementation techniques are summarized, and some matters requiring further consideration indicated.