Parameter and state estimation may be formulated as a nonlinear minimisation problem, and many iterative techniques are available to perform the minimisation. However, the class of techniques using curvature has received little attention in the past, largely a result of excessive computational difficulties and convergence problems. In this paper, it is shown that the curvature methods are readily adaptable to parameter and state estimation, and it is also shown that the curvature methods are more rapidly convergent than other iterative techniques. Examples in linear and nonlinear parameter and state estimation serve to illustrate the advantages of the curvature methods.
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Graham C. Goodwin (1969) studied this question.
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