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Dynamic data reconciliation problems are discussed from the perspective of the mathematical theory of ill-posed inverse problems. Regularization is of crucial importance to obtain satisfactory estimation quality of the reconciled variables. Usually, some penalty is added to the least-squares objective to achieve a well-posed problem. However, appropriate discretization schemes of the time-continuous problem act themselves as regularization, reducing the need of problem modification. Based ondoi:10.1016/s0959-1524(01)00021-x fatcat:ujfde4karrdnfazolyoggy4ysa