Discrete Event Process Modeling of Manufacturing Systems Using Sensor Graphs
Doctoral thesis, 2009
The design of control programs for manufacturing systems
is becoming more and more complex as the demands for flexibility,
efficiency and reconfigurability increase, due to
changing consumer demands and fierce competition.
There are methods stemming from academia that can assist the control programmers
in facing these challenges. Some of those methods require a formal model
of the system to be controlled.
This thesis presents the language
for modeling systems
that are to be controlled by a PLC.
The system under control, the
, is typically mechanical,
containing equipment such as lifts, fixtures and robots, as
well as mobile objects like pallets and manufacturing parts.
The controller observes the state of the process
through binary position sensors and influences it through binary control signals.
The Sensor Graph model describes, as a discrete event system,
how the physical objects activate
and deactivate the sensors under the influence of control signals.
The purpose of the suggested language is to make modeling easier and less fallible for the kind of systems described above, compared to existing general purpose discrete event languages.
The language has a graphical syntax that often makes the models more compact
and concise than models expressed using classical state machine-
or Petri net-based languages.
It does also support hierarchical and component-based modeling.
It is shown how a closed-loop system can be formally verified based
on a Sensor Graph process model and a discrete state equation representing
the PLC program.
It is also shown how the Sensor Graph process model can be translated
into an observer that provides the controller with an estimate of the process' state.
This state estimate is used for state feedback control and automated fault monitoring.
The semantics of Sensor Graphs takes care of the details concerning the
interaction between the discrete event process and the
for instance the computation delay between the
controller's input sampling and its output response, and the timing of the
process in relation to the controller.
Fault Detection and Diagnosis
Discrete Event Systems
State Feedback Control
EF-salen, Hörsalsvägen 11, Chalmers
Opponent: Prof. Lawrence E. Holloway, Department of Electrical and Computer Engineering,University of Kentucky, Lexington, USA