Numerical Data Fitting in Dynamical Systems: A Practical Introduction with Applications and Software
Numerical Data Fitting in Dynamical Systems: A Practical Introduction with Applications and Software
Fault Diagnosis: Models, Artificial Intelligence, Applications
Fault Diagnosis: Models, Artificial Intelligence, Applications
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The paper considers the problem of determining an optimal observation schedule for discrimination between competing models of a dynamic process. To this end, an approach originating in optimum experimental design is applied. Its use necessitates solving some maximin problem. Unfortunately, a high computational cost is the main reason for limited practical applications, especially regarding distributed parameter systems. The paper constitutes an attempt to overcome such an impediment via a parallel implementation performed on a Linux cluster. The resulting numerical scheme is validated on a simulation example motivated by problems arising in chemical kinetics.