 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 unmeasured 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
