The success of the
system engineering cycle strongly depends on a multitude of
analytical tasks that need to be accomplished in synchronization
with the system engineering tasks. These analytical tasks can
best be summarized as follows:
The target here is
to provide detailed enough but still reliable mathematical
presentation of the system dynamics relevant for stability and
performance. In this regard previous experience and good
engineering sense are advantageous assets in order to reach the
most suitable system model. In many cases a multitude of system
models are derived, each used for a certain purpose.
When the parameters
of a given system are not known and can’t be calculated in a
reliable manner, it is possible to identify these parameters
applying system identification experiments that involve system
excitation using appropriately designed signals and finding the
correlation between these signal and the resulted measurements.
The identified model can then substitute or complement any
analytically derived model.
At first a dynamic
system needs to be analyzed for stability and performance. This
analysis is usually done using the previously obtained system
model. To obtain the required stability coupled with a
favorable dynamic performance, the system needs to be
controlled using the most suitable controller type, which
depends on the system nature, available measurements and
possible actuation.
The complete system,
together with the suggested controller, is simulated using the
appropriate simulation application to validate its performance.
Usually, this step results on some feedback on the system and/or
the controller design.
The integration of
the different sensors and actuators within the system is a
delicate job that strongly influences system controllability and
observability. Good sensor and actuator configuration is
essential for a successful dynamic system. A usual part of this
job is the design of the measurement and actuation chains and
their appropriate signal conditioning.
