Bond Graph Modelling of Engineering Systems: Theory, Applications and Software Support

✍ Scribed by Wolfgang Borutzky (editor)

• Publisher: Springer
• Year: 2011
• Tongue: English
• Leaves: 446
• Category: Library

✦ Synopsis

The author presents current work in bond graph methodology by providing a compilation of contributions from experts across the world that covers theoretical topics, applications in various areas as well as software for bond graph modeling.

It addresses readers in academia and in industry concerned with the analysis of multidisciplinary engineering systems or control system design who are interested to see how latest developments in bond graph methodology with regard to theory and applications can serve their needs in their engineering fields.

This presentation of advanced work in bond graph modeling presents the leading edge of research in this field. It is hoped that it stimulates new ideas with regard to further progress in theory and in applications.

✦ Table of Contents

Foreword
Preface
Acknowledgements
Contents
Contributors
Abbreviations
Part I Bond Graph Theory and Methodology
1 Concept-Oriented Modeling of Dynamic Behavior
P.C. Breedveld
1.1 Introduction
1.2 Graph-Theoretic Foundation of Bond Graphs
1.2.1 Introduction
1.2.2 Bond Graphs
1.2.3 Ports and Bonds
1.2.4 Causal Stroke
1.3 Categorization of Nodes
1.3.1 Introduction
1.3.2 Power Discontinuous Nodes
1.3.3 Power Continuous Nodes
1.3.4 Basic Elements
1.3.5 Model Transformation into a Bond Graph
1.4 Computational Causality and Causality Assignment
1.4.1 Introduction
1.4.2 Causal Port Properties
1.4.3 Causality Assignment
1.4.4 Causality Assignment Example
1.5 Port-Based Physical System Modeling
1.5.1 Introduction
1.5.2 Basic Physical Principles
1.5.3 Modeling Versus Model Transformation
1.5.4 Model Representations
1.5.5 The Concepts of System Boundary and Environment
1.5.6 The Concepts of State, Equilibrium, and Change of State
1.5.7 Boundary Criteria
1.5.8 The Port Concept
1.5.9 Bond Graph Construction
1.5.10 Energy Conservation
1.5.11 The Power Port Concept and the Bond Graph Notation
1.5.12 Causality, Legendre Transforms, and Co-energy
1.5.13 The Thermodynamic Versus the Mechanical Framework of Variables
1.5.14 Energy States Versus Configuration States
1.5.15 Conservation and Continuity Within a Domain
1.6 Conclusion
References
2 Energy-Based Bond Graph Model Reduction
L.S. Louca, D.G. Rideout, T. Ersal, and J.L. Stein
2.1 Introduction
2.2 Model Reduction Metrics
2.2.1 Activity: A Metric for Assessing Aggregate Energy Flow
2.2.2 Relative Activity
2.2.3 Energetic Contribution Index (ECI)
2.3 Model Reduction Algorithms
2.3.1 Model Order Reduction Algorithm (MORA)
2.3.2 Decoupling Identification and Partitioning Algorithm
2.3.3 ECI-Based Model Reduction Algorithm
2.4 Case Studies
2.4.1 Reduction of a Heavy Tractor Semi-trailer and a Hybrid Hydraulic Truck Using MORA
2.4.2 Partitioning of a Nonlinear Pitch Plane Truck Model
2.4.3 ECI-Based Reduction of a HMMWV Model
2.5 Discussion
2.6 Conclusion
References
3 LFT Bond Graph Model-Based Robust Fault Detectionand Isolation
M.A. Djeziri, B. Ould Bouamama, G. Dauphin-Tanguy,and R. Merzouki
3.1 Introduction
3.2 Bond Graph Modeling in LFT Form
3.2.1 LFT Representation
3.2.2 LFT Modeling of Bond Graph Elements
3.2.3 LFT BG of a Global Model
3.2.4 Example
3.3 LFT Bond Graphs for Robust FDI
3.3.1 Generation of Robust Residuals
3.3.2 Sensitivity Analysis
3.4 Application to a Mechatronic System
3.4.1 Robust FDI Procedure
3.4.2 Simulation Results
3.4.3 Experimental Results
3.5 Conclusion
References
4 Incremental Bond Graphs
Wolfgang Borutzky
4.1 Introduction
4.2 Basics of Incremental Bond Graphs
4.2.1 Incremental Models of Bond Graph Elements
4.2.2 Derivation of Output Sensitivity Functions from an Incremental Bond Graph
4.3 Direct and Inverse Models
4.3.1 Direct Models
4.3.2 Inverse Models
4.4 Parameter Sensitivities of Transfer Functions from Direct Bond Graph Models
4.4.1 Example: Coupled Hydraulic Tanks
4.4.2 Example: Fixed Field DC Motor
4.4.3 Bond Graphs with Linear Multiport Fields
4.5 Parameter Sensitivities of Transfer Functions of Linear Inverse Models
4.5.1 Construction of the Bond Graph of the Inverse Model
4.5.2 Construction of the Incremental Bond Graph of the Inverse Model
4.5.3 Matrix-Based Determination of Transfer Function Sensitivities for the Inverse Model
4.5.4 Example: Inverse Model of a Linear Network
4.5.5 Example: Inverse Model of a Fixed Field DC Motor
4.6 Parameter Sensitivities of ARR Residuals
4.6.1 ARRs for Continuous Systems
4.6.2 ARRs for Hybrid Systems
4.6.3 Determination of Parameter Sensitivities of ARR Residuals
4.6.4 Example: Analog Integrator
4.7 Conclusions
Appendix
References
Part II Bond Graph Modelling for Design, Control, and Diagnosis
5 Coaxially Coupled Inverted Pendula: Bond Graph-Based Modelling, Design and Control
P.J. Gawthrop and F. Rizwi
5.1 Introduction
5.2 Qualitative System Analysis and Design
5.2.1 Controllability
5.2.2 Poles and Zeros
5.3 Quantitative System Analysis and Design
5.4 Control System Design
5.5 Experimental Results
5.6 Conclusions
References
6 Bond Graphs and Inverse Modeling for Mechatronic System Design
Wilfrid Marquis-Favre and Audrey Jardin
6.1 Introduction
6.2 Theoretical Concepts
6.2.1 Model Inversion
6.2.2 Concepts of Structural Analysis
6.2.3 Structural Analysis Concepts in Bond Graph
6.3 Criteria for Inversion and Analysis Levels
6.3.1 Invertibility Criteria
6.3.2 Differentiability Criterion
6.3.3 Bicausality Assignment Procedure
6.3.4 Notion of Analysis Levels
6.4 Phases of the Sizing Methodology
6.4.1 Validity of the Design Model
6.4.2 Validity of the Specifications
6.4.3 Component Specification and Selection
6.4.4 Selected Component Validation
6.4.5 Open-Loop Control Determination
6.5 Conclusion
References
7 Bond Graph Model-Based Fault Diagnosis
S.K. Ghoshal and A.K. Samantaray
7.1 Introduction
7.2 Bond Graph Model-Based Qualitative Diagnosis
7.2.1 Knowledgebase Construction
7.2.2 Determination of Initial Fault Set
7.2.3 Example of Qualitative Diagnosis
7.3 Qualitative Diagnosis Through Tree Graphs
7.4 Qualitative Diagnosis Through Temporal Causal Graphs
7.4.1 Hypothesis Generation
7.4.2 Hypothesis Validation
7.5 Bond Graph Model-Based Quantitative Diagnosis
7.5.1 Diagnostic Bond graphs and Residual Sinks
7.5.2 An Example Application
7.5.3 Generalized ARRs for Hybrid Systems
7.5.4 Adaptive Thresholds and Residual Post-processing
7.6 Unknown Input Observers
7.7 Concluding Remarks
References
Part III Applications
8 Bond Graph Modeling and Simulation of Electrical Machines
Sergio Junco and Alejandro Donaire
8.1 Introduction
8.2 Bond Graphs from Classical Equivalent Circuit Models of Electrical Machines
8.2.1 DC-Machines: Brushed DC-Motors: Separately, Parallel, Series, and Compound Excited DC-Motors
8.2.2 AC-Machines: Synchronous and Asynchronous or Induction Machines
8.2.3 Motors for Low-Power Drives: Permanent Magnet Synchronous Motor, Brushless DC-Motors, Synchronous Reluctance, and Permanent Magnet Stepper Motors
8.3 Constructing BG Models of Electrical Machines from Physical Principles
8.3.1 BG Models of the IM Explicitly Displaying Magnetic Phenomena
8.3.2 BG Modeling of Electrical Machines Based on Energy Conservation Principles
8.4 BG-Based Simulation of Electrical Drives
8.4.1 First Experiment: IM Behavior Undergoing Free Acceleration from Stall, Stepwise Loading, and Speed Reversal
8.4.2 Second Experiment: IM Behavior as Part of an Electrical Drive
8.5 Conclusions
References
9 Simulation of Multi-body Systems Using Multi-bond Graphs
Jesus Felez, Gregorio Romero, Joaquín Maroto, and María L. Martinez
9.1 Introduction
9.2 Modeling Multi-body Systems
9.2.1 Multi-bond Graph Formulation
9.2.2 Modeling Rigid Bodies
9.2.3 Kinematic Constraints
9.3 Methods for Obtaining the Dynamic Equations
9.3.1 The Lagrange Multipliers Method
9.3.2 The ZCPs Opening Method
9.3.3 Mathematical Difficulties to Solve Systems with ZCPs
9.3.4 Algorithms for Solving Systems with ZCPs in One-Dimensional Bond Graphs
9.3.5 Multi-bond Graph Systems with Topological Loops
9.3.6 Application Example
9.4 Conclusions
References
10 Bond Graph Modelling of a Solid Oxide Fuel Cell
P. Vijay, A.K. Samantaray, and A. Mukherjee
10.1 Introduction
10.2 Bond Graph Model of the SOFC
10.2.1 Process Description and Modelling Approach
10.2.2 Modelling Assumptions
10.2.3 Storage of a Two-Species Gas Mixture
10.2.4 An Entropy-Generating R-field to Represent the Convection of a Gas Mixture
10.2.5 True Bond Graph Model of the SOFC
10.3 Open- and Closed-Loop Dynamic Simulations
10.3.1 Model Initialisation
10.3.2 Static Characteristics
10.3.3 Dynamic Responses
10.4 Conclusions
References
Part IV Software for Bond Graph Modelling and Simulation
11 Automating the Process for Modeling and Simulation of Mechatronics Systems
Jose J. Granda
11.1 Introduction
11.2 Fundamental Methods to Generate Models
11.2.1 Modeling Process with Block Diagrams
11.2.2 Modeling Process with Direct Programming and Integration of the Differential Equations
11.2.3 Automating the Modeling Process Using Bond Graphs
11.2.4 Mathematical Equivalence Between the Block Diagram Method and the Bond Graph Method
11.3 Implementing the Automated Process Using Different Software Tools
11.3.1 The CAMPG/SYSQUAKE Interface
11.3.2 CAMPG/MATLAB Interface
11.3.3 The CAMPG/SIMULINK Interface
11.4 Automatically Generated Block Diagrams from Bond Graph Models
11.4.1 Principles Behind the Generation of Block Diagrams from Bond Graphs
11.4.2 Block Diagrams from CAMPG
11.4.3 Building an Organized Block Diagram with Submodels from Bond Graphs: From Computer-Generated Subsystems
11.5 Chapter Summary
References
Index