Coaxially Coupled Inverted Pendula: Bond Graph-Based Modelling, Design and Control

2011 ◽  
pp. 179-194
Author(s):  
P.J. Gawthrop ◽  
F. Rizwi
Keyword(s):  
Bond Graph ◽  
And Control

Representation of Measured Ejector Characteristics by Simple Eulerian Bond Graph Models

1985 ◽  
Vol 107 (4) ◽  
pp. 258-261 ◽  
Author(s):  
H. M. Paynter
Keyword(s):  
Power Plants ◽  
Bond Graph ◽  
Nuclear Industry ◽  
Graph Models ◽  
Design Data ◽  
Fluidic Devices ◽  
Jet Pumps ◽  
Fixed Constant ◽  
And Control ◽  
Support Facility

Ejectors (or jet pumps) are highly reliable pure fluidic devices very commonly used in power plants, propulsion systems, petrochemical processes and other thermofluid systems. However, little off-design data has been available in a form suitable for dynamic simulation and control system design. Fortunately, concerns of the nuclear industry have recently led the Idaho National Engineering Laboratory (INEL) to obtain, from their LOFT Test Support facility, ejector test data sufficiently extensive to formulate a complete model accurately describing all flow conditions. Thus an elementary fixed-constant bond graph structure will approximate complete ejector characteristics, while a model only slightly more complex fits all INEL data within experimental scatter.

Application of Vector Bond Graphs to the Modeling of a Class of Hand Prostheses

Volume 3 ◽  
2004 ◽  
Author(s):  
Anand Vaz ◽  
Shinichi Hirai
Keyword(s):  
Three Dimensional ◽  
Graph Model ◽  
Systems Design ◽  
Bond Graph ◽  
Bond Graphs ◽  
Prosthetic Joints ◽  
Angular Velocities ◽  
Control Systems Design ◽  
And Control ◽  
Systematic Derivation

Vector bond graphs have been systematically applied to the modeling of prosthesis for a partially impaired hand. The partial impairment considered covers a category of the hand that has lost one or more fingers but retains the ability of its remaining natural fingers. The fingers and their prosthetic extensions are considered as rigid links. Rotation matrices which specify orientation of finger links are obtained from respective angular velocities. String-tube mechanism used to actuate prosthetic joints is modeled with the connection to joint variables of the mechanism. The vector bond graph approach enables the modeling of three dimensional movement of the hand mechanism. An example of a two joint string-tube actuated prosthetic mechanism is presented to describe the construction of the vector bond graph model. Systematic derivation of dynamics from the vector bond graphs is shown. The approach based on vector bond graphs presented here is useful for simulations and control systems design of such biomechanical systems.

scholarly journals Brushless DC Motor Modeling Using Bond Graph Method and Control using LabVIEW

1970 ◽  
Vol 5 (1.) ◽  
Author(s):  
Ammar Alsabbagh ◽  
Péter Tamás Szemes ◽  
Abdulkader Baki
Keyword(s):  
Dynamic Model ◽  
Pid Controller ◽  
Dc Motor ◽  
Bond Graph ◽  
Brushless Dc Motor ◽  
Graph Method ◽  
Brushless Dc ◽  
Three Phase ◽  
Labview Program ◽  
And Control

This paper aims to simulate and control a three-phase Brushless DC Motor. Bond Graph method has been used to obtain fast and simple dynamic model. The system has been controlled by classical PID controller. All the paper results were fulfilled using LabVIEW program.

scholarly journals Complementary Use of BG and EMR Formalisms for Multiphysics Systems Analysis and Control

2012 ◽  
Author(s):  
Zeineb Chikhaoui ◽  
Julien Gomand ◽  
François Malburet ◽  
Pierre-Jean Barre
Keyword(s):  
Flight Control ◽  
Systems Analysis ◽  
Control Structure ◽  
Bond Graph ◽  
Modeling And Analysis ◽  
Helicopter Flight ◽  
Lumped Parameter ◽  
Lumped Parameter Modeling ◽  
Definition Of ◽  
And Control

In this paper, a complex multiphysics system is modeled using two different energy-based graphical techniques: Bond Graph and Energetic Macroscopic Representation. These formalisms can be used together to analyze, model and control a system. The BG is used to support physical, lumped-parameter modeling and analysis processes, and then EMR is used to facilitate definition of a control structure through inversion-based methodology. This complementarity between both of these tools is set out through a helicopter flight control subsystem.

Planar, Large Excursion Bond Graph Model for Full Suspension Mountain Biking

2005 ◽  
Author(s):  
Robin C. Redfield
Keyword(s):  
Initial Conditions ◽  
Contact Point ◽  
Graph Model ◽  
Bond Graph ◽  
Mountain Bike ◽  
Dynamic Interactions ◽  
Dynamics And Control ◽  
Ground Profile ◽  
And Control ◽  
Main Frame

A bond graph model of a fully suspended mountain bike and non-seated rider is created to develop predictions for the performance of mountain bikes during large excursion maneuvers such as drops, jumps, crashes, and rough terrain riding. The model assumes planar dynamics, a single pivot full suspension bicycle, and a rigid-body rider suspended from the bicycle. The main frame, front fork, rear triangle, two wheels, and rider are modeled as separate bodies interconnected at the main pivot, telescoping fork, pedals, handlebars, and axles. Suspensions are between the main frame and front fork, main frame and rear triangle, handlebars and rider (arms) and pedals and rider (legs). An algorithm is used to allow tracking of a virtual tire-ground contact point for events that separate the wheels from the ground. Significant excursions of motion are allowed to model major slope changes, separations from the ground, and large rotational events (endos). The bond graph approach allows kinematics to drive the significant dynamic interactions with the effort (force and torque) relationships being derived for “free”. Simulations of a ground profile with a rise followed by a steep drop are performed for various initial conditions to qualitatively validate the predictions of the model. Rider strategies for negotiating the drop are examined in the process. Overarching goals of the research are to examine and understand the dynamics and control of interactions between a cyclist and mountain bike. Specific, longer term, goals are to understand the improvement in performance afforded by an experienced rider, to hypothesize human control algorithms that allow riders to perform maneuvers well and safely, to predict structural bike and body forces from these maneuvers, and to quantify performance differences between hard-tail and various full suspension bicycles.

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