A new line of research has been recently activated in the field of modeling: the Power-Oriented Graphs. It is a theoretical work devoted to the developments of a tool for modeling general complex dynamical systems. Moreover, CAD tools for the simulation of dynamical systems and the design of control systems have been developed and are currently utilized with profit in research activities at DEIS.
From an engineering point of view, it is very important to have a "good'' model of the system one is dealing with. In fact, a good model gives insights into the real structure of the system and allows a deep understanding of its potentialities from a "dynamic'' point of view. When the system is simple, the modeling process can be very easy, but when the system becomes bigger and more complex (as, for example, when a large number of small sub-systems interact together), the modeling process can become quite complex.
The Power-Oriented Graphs (POG) and "signal flow graph'', are a graphical and mathematical modeling technique suitable for modeling real systems. This technique is based on the same Bond Graph idea (by Paynter, Karnopp and Rosenberg) to use the "power interaction'' between sub-systems as basic concept for modeling. Compared with the Bond Graphs, the POG technique has a different graphical notation and it is more mathematically oriented.
A POG is essentially based on two blocks: an "elaboration block'' which stores and/or dissipates energy, and a "connection block'' which can "only transform'' the energy, that is, transform the system variables from one type of energy-field to another. Main characteristics of the POG technique: direct correspondence between POG blocks and real physical parts of the system; suitable for representing both scalar and vectorial systems; the POG schemes can be easily graphically and mathematically transformed; the state space mathematical model of a system can be obtained "directly'' from the corresponding POG representation; when some dynamic parameters of the system tend to zero (or to infinity), the "reduced'' POG model can be easily obtained by using a proper "congruent transformation''.
The POG technique has been successfully used for modeling systems like, for example, brushless motors, asynchronous motors, n-links manipulators, robotic systems.
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