Some Key Issues in Using Bond Graphs and Genetic Programming for Mechatronic System Design

2001 ◽  
Author(s):  
R. C. Rosenberg ◽  
E. D. Goodman ◽  
Kisung Seo
Keyword(s):  
Genetic Programming ◽  
System Design ◽  
Design Space ◽  
Bond Graph ◽  
Mechatronic System ◽  
Bond Graphs ◽  
Mechatronic Systems ◽  
Energy Behavior ◽  
Key Issues ◽  
Bond Graph Modeling

Abstract Mechatronic system design differs from design of single-domain systems, such as electronic circuits, mechanisms, and fluid power systems, in part because of the need to integrate the several distinct domain characteristics in predicting system behavior. The goal of our work is to develop an automated procedure that can explore mechatronic design space in a topologically open-ended manner, yet still find appropriate configurations efficiently enough to be useful. Our approach combines bond graphs for model representation with genetic programming for generating suitable design candidates as a means of exploring the design space. Bond graphs allow us to capture the common energy behavior underlying the several physical domains of mechatronic systems in a uniform notation. Genetic programming is an effective way to generate design candidates in an open-ended, but statistically structured, manner. Our initial goal is to identify the key issues in merging the bond graph modeling tool with genetic programming for searching. The first design problem we chose is that of finding a model that has a specified set of eigenvalues. The problem can be studied using a restricted set of bond graph elements to represent suitable topologies. We present the initial results of our studies and identify key issues in advancing the approach toward becoming an effective and efficient open-ended design tool for mechatronic systems.

A System Framework With Online Monitoring and Evaluation for Design Evolution of Engineering Systems

2010 ◽  
Vol 10 (3) ◽  
Author(s):  
L. B. Gamage ◽  
C. W. de Silva
Keyword(s):  
Genetic Programming ◽  
Domain Knowledge ◽  
Design Space ◽  
Graph Model ◽  
Bond Graph ◽  
Design Solution ◽  
Engineering Systems ◽  
Design Evolution ◽  
Bond Graph Modeling ◽  
Machine Health Monitoring

This paper presents a methodology for the design evolution of engineering systems, with a mechatronic emphasis. The developed approach specifically integrates machine health monitoring and an expert system and carries out the design evolution of a multidomain dynamic system using bond graph modeling and genetic programming. The evolution of a bond graph model of a mechatronic system through genetic programming enables the exploration of the design space, thereby generating a global optimum design solution in an automated manner. Domain knowledge and expertise are used to control the design exploration and to restrict it only to a meaningful design space. As an illustrative example, the developed methodology is applied to redesign the electrohydraulic manipulator of an existing industrial fish processing machine.

Demonstrating the Generation of Bond Graphs From 3D Assemblies

2020 ◽  
Author(s):  
Corey J. Alicchio ◽  
Justin S. Vitiello ◽  
Pradeep Radhakrishnan
Keyword(s):  
Bond Graph ◽  
Dynamic Responses ◽  
Bond Graphs ◽  
Mechatronic Systems ◽  
3D Cad ◽  
Related Information ◽  
Grammar Rules ◽  
Gear Trains ◽  
System Graph ◽  
Future Work

Abstract The bond graph method provides a generic and simple way to compute differential equations and dynamic responses for complex mechatronic systems. This paper will illustrate the process of automatically generating bond graphs from 3D CAD assemblies of gear-trains. Using appropriate CAD application programming interfaces (APIs), information on parts and mates within an existing assembly is extracted. The extracted information is stored as an identity graph, which also stores all geometry and mass related information of every part. Grammar rules are then used to transform the identity graph to a system graph, which is then converted to bond graph using an existing bond graph generation program. The paper will discuss the process, challenges and planned future work.

Function Basis for Mechatronic System Design

2011 ◽  
Vol 284-286 ◽  
pp. 1401-1407
Author(s):  
Yong Xu
Keyword(s):  
Information Processing ◽  
System Design ◽  
Theoretical Basis ◽  
State Transition ◽  
Transformation Function ◽  
Mechatronic System ◽  
Mechatronic Systems ◽  
Design Models ◽  
Functional Description ◽  
Function Transformation

A new function-oriented theoretical basis for mechatronic system design is presented in the paper, with a technology-independent functional description of such aspects in a mechatronic system as 1) relations and distinctions among purpose function, transformation function and state transition and 2) structure of information processing. All discussions are summarized in a set of principles, which consequently form the basis for devising design models and methods for mechatronic systems.

scholarly journals Modeling of Dynamical System Piloted by Discrete Subsystem Based on Bond Graph Approach

2017 ◽  
Vol 7 (5) ◽  
pp. 2902
Author(s):  
Ben Salem J ◽  
Lakhoua M.N. ◽  
El Amraoui L
Keyword(s):  
Dynamical System ◽  
Digital Computer ◽  
Bond Graph ◽  
Design Technique ◽  
Mechatronic System ◽  
Mechatronic Systems ◽  
Braking System ◽  
Structured Analysis ◽  
Analysis Design

This paper is a contribution to the analysis and modeling of a mechatronic system with dynamic behavior that is controlled by a digital computer. In this paper, a bibliographic research on mechatronic systems is presented by specifying a case study of the Anti-lock Braking System (ABS). Then, a methodology of systemic modeling of the ABS system based on two methods Structured Analysis Design Technique (SADT) and bond graph (BG) is proposed. The model created is validated with three software programs:  CarSim, 20 Sim and Simulink.

Presenting a Multi-Level Superstructure Optimization Approach for Mechatronic System Design

2010 ◽  
Author(s):  
Henrik C. Pedersen ◽  
Torben O. Andersen ◽  
Michael R. Hansen ◽  
Michael M. Bech
Keyword(s):  
System Design ◽  
Integrated Design ◽  
Design Approach ◽  
Optimization Approach ◽  
Mechatronic System ◽  
Mechatronic Systems ◽  
Analysis And Design ◽  
Basic Set ◽  
Multi Level ◽  
Multidisciplinary System

Synergism and integration in the design process is what sets apart a Mechatronic System from a traditional, multidisciplinary system. However the typical design approach has been to divide the design problem into sub problems for each technology area (mechanics, electronics and control) and describe the interface between the technologies, whereas the lack of well-established, systematic engineering methods to form the basic set-off in analysis and design of complete mechatronic systems has been obvious. The focus of the current paper is therefore to present an integrated design approach for mechatronic system design, utilizing a multi-level superstructure optimization based approach. Finally two design examples are presented and the possibilities and limitations of the approach are outlined.

Bond Graph modeling for fault detection and isolation of a train door mechatronic system

2016 ◽  
Vol 49 ◽  
pp. 212-224 ◽  
Author(s):  
Laurent Cauffriez ◽  
Sébastien Grondel ◽  
Pierre Loslever ◽  
Christophe Aubrun
Keyword(s):  
Fault Detection ◽  
Bond Graph ◽  
Fault Detection And Isolation ◽  
Mechatronic System ◽  
Graph Modeling ◽  
Bond Graph Modeling

scholarly journals Simultaneous Kinematic and Contact Force Modeling of a Human Finger Tendon System Using Bond Graphs and Robotic Validation

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
James A. Tigue ◽  
Raymond J. King ◽  
Stephen A. Mascaro
Keyword(s):  
Bond Graph ◽  
Contact Forces ◽  
Free Motion ◽  
Force Transmission ◽  
Bond Graphs ◽  
Moment Arms ◽  
Static Contact ◽  
Surface Contact ◽  
Bond Graph Modeling ◽  
Contact Experiments

Abstract This paper aims to use bond graph modeling to create the most comprehensive finger tendon model and simulation to date. Current models are limited to either free motion without external contact or fixed finger force transmission between tendons and fingertip. The forward dynamics model, presented in this work, simultaneously simulates the kinematics of tendon-finger motion and contact forces of a central finger given finger tendon inputs. The model equations derived from bond graphs are accompanied by nonlinear relationships modeling the anatomical complexities of moment arms, tendon slacking, and joint range of motion (ROM). The structure of the model is validated using a robotic testbed, Utah's Anatomically correct Robotic Testbed (UART) finger. Experimental motion of the UART finger during free motion (no external contact) and surface contact are simulated using the bond graph model. The contact forces during the surface contact experiments are also simulated. On average, the model was able to predict the steady-state pose of the finger with joint angle errors less than 6 deg across both free motion and surface contact experiments. The static contact forces were accurately predicted with an average of 11.5% force magnitude error and average direction error of 12 deg.

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