AE xxx Modeling and Simulation
Laboratory 1.5 0 2 5
Mar. 11, 2008
Prerequisites: NIL
Introduction:
Objectives, concepts and types of models.
Modelling: Analytical
and experimental modeling of simple mechanical, hydraulic,
thermal and structural systems. Transfer function and block
diagram
representation.
Time response: First
and second order systems. System
representation and
simulation using MATLAB, SIMULINK and AMESim tools.
Quantifying Uncertainty:
Use of simulation to quantify the uncertainty in system response and
performance caused by uncertainty in model parameters and inputs.
Special topic:
Software simulation of stiff systems
and
impact of integration time step on methodology and response.
Lab project:
Application of modelling and simulation methodologies to a complex
engineering system.
References:
K. Ogata, System Dynamics, 4th ed. Pearson Education LPE, 2004.
E. O. Doebelin, System Dynamics : modeling, analysis, simulation, design
New York: Marcel Dekker, 1998.
User Manuals for the Setups & AMESim Engg. System Modelling &
Simulation
Software Tool
List of experiments:
Servo Systems : DC Motor, Rotary
Servo & Gyro Platform; Step
response for time constant & DC gain
Thermal Systems : Heating of metal block &
Heating of air;
step response for time constant, DC gain & transport lag due to
sensor
Level/Flow System : Tank level & flow rate models, with time
constant & DC gain; Issue of linearization
Torsion Disk System: Free-free and restrained elastic system
models; Natural frequency & damping; Mass
stiffness & damping evaluation
Pendulum Experiment: Normal & Inverted pendulum; coupled 2-DOF
model for cart & pendulum motion;Issue of
linearization, natural frequency & damping
Flexgage Experiment: Flexible Robotic arm; combined rigid body
& elastic body models through step input
MATLAB Exercises : Generation of matlab/simulink responses
for
experimentally generated models & their
comparison with experimental responses.
MATLAB Exercises : Generation of matlab/simulink responses
for
theoretically generated models & their
comparison with experimental responses
Random Simulation : Sampling of system parameters, in selected
experiments conducted by all batches, and
generation of a family of responses for
the applicable inputs. Statistical analysis
of the simulated responses to characterize
the overall quantities e.g. mean response,
variance etc.
Stiff Simulation : Use the data for flexgage to identify
time
scales for rigid & elastic body dynamics.
solution using two different time steps &
comparison of solution time and solution
accuracy.