Model-based tools have the potential to significantly improve the process of developing novel cyber-physical systems (CPS). In this paper, we consider the question of what language features are needed to model such systems. We use a small, experimental hybrid systems modeling language to show how a number of basic and pervasive aspects of cyber-physical systems can be modeled concisely using the small set of language constructs. We then consider four, more complex, case studies from the domain of robotics. The first, a quadcopter, illustrates that these constructs can support the modeling of interesting systems. The second, a serial robot, provides a concrete example of why it is important to support static partial derivatives, namely, that it significantly improves the way models of rigid body dynamics can be expressed. The third, a linear solenoid actuator, illustrates the languageās ability to integrate multiphysics subsystems. The fourth and final, a compass gait biped, shows how a hybrid system with non-trivial dynamics is modeled. Through this analysis, the work establishes a strong connection between the engineering needs of the CPS domain and the language features that can address these needs. The study builds the case for why modeling languages can be improved by integrating several features, most notably, partial derivatives, differentiation without duplication, and support for equations. These features do not appear to be addressed in a satisfactory manner in mainstream modeling and simulation tools.

VL - 7 ER - TY - Generic T1 - Acumen: An open-source testbed for cyber-physical systems research T2 - EAI International Conference on CYber physiCaL systems, iOt and sensors Networks Y1 - 2015 A1 - Walid Taha A1 - Adam Duracz A1 - Yingfu Zeng A1 - Kevin Atkinson A1 - Ferenc A.Bartha A1 - Paul Brauner A1 - Jan Duracz A1 - Fei Xu A1 - Robert Cartwright A1 - Michal Konecny A1 - Eugenio Moggi A1 - Jawad Masood A1 - Pererik Andreasson A1 - Jun Inoue A1 - Anita Santanna A1 - Roland Philippsen A1 - Alexandre Chapoutot A1 - O'Malley, M.K. A1 - Aaron Ames A1 - Veronica Gaspes A1 - Lise Hvatum A1 - Shyam Mehta A1 - Henrik Eriksson A1 - Christian Grante JF - EAI International Conference on CYber physiCaL systems, iOt and sensors Networks ER - TY - Generic T1 - Modeling Basic Aspects of Cyber-Physical Systems, Part II T2 - The Fourth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob'13) Y1 - 2013 A1 - Yingfu Zeng A1 - Rose, Chad G. A1 - Paul Branner A1 - Walid Taha A1 - Jawad Masood A1 - Roland Philippsen A1 - Marcia K. O'Malley A1 - Robert Cartwright AB -We continue to consider the question of what

language features are needed to effectively model cyber-physical

systems (CPS). In previous work, we proposed using a core

language as a way to study this question, and showed how

several basic aspects of CPS can be modeled clearly in a

language with a small set of constructs. This paper reports

on the result of our analysis of two, more complex, case studies

from the domain of rigid body dynamics. The first one, a

quadcopter, illustrates that previously proposed core language

can support larger, more interesting systems than previously

shown. The second one, a serial robot, provides a concrete

example of why we should add language support for static

partial derivatives, namely that it would significantly improve

the way models of rigid body dynamics can be expressed.

JF - The Fourth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob'13)
CY - Tokyo, Japan
ER -
TY - Generic
T1 - Mathematical Equations as Executable Models of Mechanical Systems
Y1 - 2010
A1 - Angela Yun Zhu
A1 - Edwin Westbrook
A1 - Jun Inoue
A1 - Alexandre Chapoutot
A1 - Cherif Salama
A1 - Marisa Peralta
A1 - Travis Martin
A1 - Walid Taha
A1 - Robert Cartwright
A1 - O'Malley, M.K.
AB - Cyber-physical systems comprise digital components that directly interact with a physical environment. Specifying the behavior desired of such systems requires analytical modeling of physical phenomena. Similarly, testing them requires simulation of continuous systems. While numerous tools support later stages of developing simulation codes, there is still a large gap between analytical modeling and building running simulators. This gap significantly impedes the ability of scientists and engineers to develop novel cyber-physical systems. We propose bridging this gap by automating the mapping from analytical models to simulation codes. Focusing on mechanical systems as an important class of models of physical systems, we study the form of analytical models that arise in this domain, along with the process by which domain experts map them to executable codes. We show that the key steps needed to automate this mapping are 1) a light-weight analysis to partially direct equations, 2) a binding-time analysis, and 3) an efficient implementation of symbolic differentiation. As such, our work pinpoints and highlights a number of limitations in the state of the art in tool support of simulation, and shows how some of these limitations can be overcome.

ER -