MESB 374 Modeling and Analysis of Dynamic System Introduction

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MESB 374 Modeling and Analysis of Dynamic
SystemIntroduction
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Example Vehicle speed control
Traction input, excitation
Gravitation disturbance
Inertia force
Friction damping
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MODEL
linearization
ANALYSIS
CONTROL
output
input
states
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Course Overview

• One of the most important and multi-disciplinary
• courses youll ever take
• Physics
• Kinematics
• Mathematics
• Time and frequency response analysis
• Engineering judgment

Leveraging previous coursework and preparing for
future coursework Mechanics, electrical,
electromechanical Fluid-thermal Calculus,
differential equations, complex
algebra Measurements/instrumentation
understanding
Emphasize combination of theoretical and
conceptual understanding
i.e. Can you explain the basic concepts to other
people?
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Basic Concepts

• System

A combination of components acting
together to perform a specific objective
Modeling
A procedure to obtain a model describing
important characteristics of system
Analysis
Investigation of performance of system,
whose model is known, under specified conditions
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Motivation for MESB 374Pervasiveness
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Definitions Related to System
Input A variable that excites a system Inputs
are not always known beforehand Inputs are
always responsible for problems in systems
Output A variable that we observe and consider
important Measurements/instrumentation Not
necessary what we want to know
State A variable that is used to describes the
internal system dynamics A set of states can
be used to fully describe systems current
situation. With two identical sets of initial
values of states, performance of a system is the
same Do you get all the states of system ?
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Different Systems/System Descriptions

• Distributed System A System with infinitely many
  state variables Continuous elastic structures
  (beams, shells, and plates)
• Fluid systems (ocean and atmosphere)
• Can often be approximately described with lumped
  models (FEM, AMM)

Lumped System A System with a finite number of
state variables Lumped parameter/ discrete
system Usually an artificial/modeling concept
Continuous-time System All the signals are
continuous in time Everything is defined at each
instant time Also called Analog systems
Discrete-time Systems Variables are only
defined at discrete times Also called sampled
data systems
Hybrid System Continuous-time discrete-time
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More Different Systems/System Descriptions

• Time-varying System (in practice)
• The characteristics of system changes with time
  going
• time-varying parameters
• time-varying dynamics

Time-invariant System (ideal) The features of
system never ever changes Usually a good
approximation for most engineering application A
good starting point to obtain main features of
system Relatively easy to analyze
Linear System Equations describing system are
linear Principle of superposition
Nonlinear System Linearize it near a operating
condition to obtain a linear approximation
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Interdisciplinary and System Nature of MESB 374
Analogous systems
Models are the same regardless of the physical
domain of interest We only need to
understand how to analyze one model, but the
results are applicable for four seemingly
different types of physical systems!



y
u
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Big Picture
Physical System
Develop Idea Model
Modeling
Not Good
No
OK
Feedback/ Feedforward Control Design
Analysis Design
Not So great
Good
Yes
Build Actual System and Verify Design
Implement on Actual System
Implementation Test
GET PAID !!
Yes
No
No
Yes
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Course Outline
Introduction
Components/ elements
Connections/ interconnects
Electrical
Mechanical
Thermal
Electromech
Hydraulic
Input/output Vs. state-variable models
Time-frequency tools of systems analysis
Feedback and system design