Computer-automated multiparadigm modeling in control systems technology
Pieter J. Mosterman, Janos Sztipanovits, and Sebastian Engell
Abstract
The use of model-based technologies has made it
imperative for the development of a feedback control system to deal
with many different tasks such as: plant modeling in all its variety;
model reduction to achieve a complexity or level of abstraction
suitable for the design task at hand; synthesis of control laws that
vary from discrete event reactive control to continuous model
predictive control, their analyses, and testing; design of the
implementation; modeling of the computational platform and its
operating system; analysis of the implementation effects; software
synthesis for different platforms to facilitate rapid prototyping,
hardware-in-the-loop simulation, etc. Throughout these tasks,
different formalisms are used that are very domain specific (e.g.,
tailored to electrical circuits, multibody systems, reactive control
algorithms, communication protocols) and that often need to be
coupled, integrated, and transformed (e.g., a block diagram control
law in the continuous domain has to be discretized and then
implemented in software). Significant improvements in many aspects
(performance, cost, development time) of the development process can
therefore be achieved by: 1) relating and integrating these different
formalisms; 2) automatic derivation of different levels of modeling
abstractions; and 3) rigorous and tailored design of the different
formalisms by capturing the domain (or meta) knowledge. The emerging
field of computer automated multiparadigm modeling (CAMPaM), presented
in this paper in the context of control system design, aims to develop
a domain-independent formal framework that leverages and unifies
different activities in each of these three dimensions.
The full paper is available from IEEE Xplore.