Pratical description of the Observers in the system engineering.

1. Massimo Talia
Electronic Engineer
Web address: http://www.taliawebs.com

2. Summary
The observers and system engineering
The observers and safety engineering
Observation and artificial intelligence
Observation vs data minig

3. The observers and system engineering
The Observers are a gray box strategy for estimating a part
or the whole system dynamics from the I/O
(Inputs/Outputs) or for isolating the faults FDI (fault
detection isolation). An Observer can be linear or
nonlinear: it’s linear if its internal structure is a linear
system; it’s nonlinear if it replicates nonlinear dynamics.
It’s deteministic if the process is deterministic, it’s
stochastic if the process is stochastic.
In the pratical applications the observer functions are
implemented in firmware or hardware or in the industrial
supervision systems.

4. The observers and safety engineering
The observers make an hardware system to look the
eventual faults ahead before having errors and failures (no
system availability).
they minimize the possibility of mistakes or trap mistakes
before the introduction of system faults (Fault Avoidance);
they increase the probability of detecting and correcting
errors before the system goes into service(Fault Detection);
They are used to ensure the system faults do not result in
system errors and/or the system errors do not lead to the
system failure (Fault tolerance).

5. Observation and artificial intelligence
The techniques of fault avoidance, fault detection,
fault tolerance make the observers to extract
knowledge from the industrial processes, complex
systems and external physical sources . In a generic
schema an observer is used as estimator and another
one as fault detector, but in the real case there are
more complex schemas and redundancy. When the
redundancy increases, the algorithm model or the
hardware become more complex. The observation is
an application of artificial intelligence system-
oriented.

6. Observation vs data mining
The observation is a technique for extracting
knowledge and information from complex physical
systems as: industrial plants, electronic boards,
mechanical or electromechanical systems, chemical
and nuclear processes and so on.
Data minig is a technique of knowledge discovery and
artificial intelligence, which is based on the extraction
of one o more data set from a Datawarehouse , in order
to improve the business processes as: the sales, the
supply chain, the human resources, the production
and so on.