Modeling

Modeling builds the structure of the system
Implementation system construct instructions
Mathematical and visual methods
Prove it. Never assume a model works.

Abstract, conceptual, graphical and/or mathematical models
"Just good enough" model (approximation)
Models don’t need to be perfect

System design

Create simple content
Common design process
Communication framework

Define system
Identify components
Equation system
- Algebraic equations
- Logical equations
- Differential equations (continuous)
- Difference equations (discrete)
Block Diagram
Simulation
Validate Results

Emergent
- new requirements
- new technologies

Multiple models

Model subsets
Different jobs, different tools.
Iterate, iterate, iterate

Implementation environment model

environment advantage
environment disadvantage
environment quirks

Parameters (constants)
States (variables)
Signals input and output values (dynamics)
- input signals
- output signals
Intermediate (internal) signals

Documentation

Complicated models need thorough document
Do not over document

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