- System Identification: System Identification methods may be
used to build mathematical models of dynamic systems based on observed
and measured input and output data from the system. System
Identification was defined by Lotfi Zadeh (1962) as: Identification is
the determination, on the basis of input and output, of a system within
a specified class of systems, to which the system under test is
equivalent.
- Optimal Estimation: Mathematical models of systems may be
used to estimate un-measured system states and parameters. Based on
mathematical models, known inputs and possibly noisy measurements, so
called State Observers may be constructed. The famous Kalman filter is
an example of an optimal minimum state estimation error variance
estimator, i.e. the Kalman filter is optimal in a minimum variance sense.
Teacher: PhD David Di
Ruscio
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