Simulate the State Changing of a Descriptor System in (Almost) Zero Time Using the Normal Probability Distribution

In number of control applications, the ability of manipulate the state vector from the input is more than vital. Thus, in the present paper, we develop analytically a methodology for the state changing of a linear control descriptor differential system based also on a linear combination of Dirac δ-function and its derivatives. Using linear algebra techniques and the generalized inverse theory, the input’s coefficients are determined. In our practical numerical application, the Dirac distribution is approximated by the normal probability distribution.

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