cbe30338-2021

Index of Python Libraries used in this Repository

cvxpy

• 4.7.4 CVXPY
• 4.7.5 $\cal{H}_2$ Optimal State Estimation
• 4.7.5 $\cal{H}_2$ Optimal State Estimation
• 4.7.6 $\cal{H}_{\infty}$ Optimal State Estimation
• 4.8.2 State Space Model
• 5.1.4 Solution using CVXPY
• 5.1.5 Solution using scipy.optimize.linprog
• 5.2.2 Solving optimization problems with CVXPY
• 5.2.3.1 Consolidating
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 6.1.3.1 Imports
• 6.2.1.2 Parameter Values
• 6.3.1 Feedforward Optimal Control
• 6.4.1 Model

matplotlib

• 1.4.6 The TCLab Plotter
• 2.1.3.1.2 Step 1. Import libraries
• 2.2.2 Steady-State Gain
• 2.2.3.1 Response to an Initial Condition
• 2.2.3.2 Time constant
• 2.2.3.3 Half-life
• 2.2.3.3 Half-life
• 2.2.3.4 Step Inputs
• 2.2.3.4 Step Inputs
• 2.2.4 Response to a step input
• 2.3.2.9 Plotting the Analytical Solution
• 2.3.3 Matching the Model to Experimental Data
• 2.4.1.1 Read data into a Pandas DataFrame
• 2.4.4 First order Energy balance model
• 2.4.6.1 Dynamics of the Heater/Sensor System
• 2.4.7.2 Standard form
• 3.2.1 Setpoint profiles
• 3.2.2.1 Specifying piecewise linear setpoint profiles
• 3.2.3.2 Representing PCR protocols in Python
• 3.9 Lab Assignment 4: Solution
• 4.1.2.1.2 Accessing Data using .columns and .fields
• 4.2.1 Output Feedback Control
• 4.4.4 Eigenvalues
• 4.6 Lab Assignment 6: Anomaly Detection
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 5.6.2 Denatured Alcohol
• 6.2.1.2 Parameter Values
• 6.3.1 Feedforward Optimal Control
• 6.4.1 Model
• 7.1.4 Ready to Roomba
• 7.1.5 Chemotaxis
• 7.2.5.1 Gantt Charts
• 7.3.1 Simulation with Simpy
• 7.5.3 Poisson Process
• 7.5.3.1 Poisson distribution
• 7.5.4 Simulating a Poisson Process in SimPy
• 7.5.6 Example: Simulation of an Order Processing Queue
• 7.5.7 Batch Processing Example (NEEDS REWORK))
• A.1.3.1 Step 1. Create the background frame.
• A.1.4 Example: Phase Plane Animation for an Exothermic Stirred-Tank Reactor

numpy

• 2.1.3.1.2 Step 1. Import libraries
• 2.2.2 Steady-State Gain
• 2.2.3.1 Response to an Initial Condition
• 2.2.3.2 Time constant
• 2.2.3.3 Half-life
• 2.2.3.3 Half-life
• 2.2.3.4 Step Inputs
• 2.2.3.4 Step Inputs
• 2.2.4 Response to a step input
• 2.3.2.9 Plotting the Analytical Solution
• 2.4.1.1 Read data into a Pandas DataFrame
• 2.4.4 First order Energy balance model
• 2.4.6.1 Dynamics of the Heater/Sensor System
• 2.4.7.2 Standard form
• 3.2.1 Setpoint profiles
• 3.2.2.1 Specifying piecewise linear setpoint profiles
• 3.2.3.2 Representing PCR protocols in Python
• 3.9 Lab Assignment 4: Solution
• 4.2.1 Output Feedback Control
• 4.2.5 Model Predictions
• 4.2.7.1 Fun with Eigenvalues
• 4.4.1 State-Space Model
• 4.6 Lab Assignment 6: Anomaly Detection
• 4.7.4 CVXPY
• 4.7.5 $\cal{H}_2$ Optimal State Estimation
• 4.7.5 $\cal{H}_2$ Optimal State Estimation
• 4.7.6 $\cal{H}_{\infty}$ Optimal State Estimation
• 4.8.2 State Space Model
• 4.8.2 State Space Model
• 5.1.4 Solution using CVXPY
• 5.1.5 Solution using scipy.optimize.linprog
• 5.2.2 Solving optimization problems with CVXPY
• 5.2.3.1 Consolidating
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 5.2.3.2 Optimal blend as a function of product specification
• 5.6.2 Denatured Alcohol
• 5.98.5.1 Data in Matrix/Vector Format
• 5.99.3 Example 19.3: Linear Programming Refinery
• 6.1.3.1 Imports
• 6.2.1.2 Parameter Values
• 6.3.1 Feedforward Optimal Control
• 6.3.3 TCLab Event Loop
• 6.4.1 Model
• 7.1.5 Chemotaxis
• 7.2.7 How many charging stations are required?
• 7.2.8 Adding a reporter process
• 7.3.1 Simulation with Simpy
• 7.5.3.1 Poisson distribution
• 7.5.6 Example: Simulation of an Order Processing Queue
• A.1.3.1 Step 1. Create the background frame.
• A.1.4 Example: Phase Plane Animation for an Exothermic Stirred-Tank Reactor

pandas

• 1.4.5 The TCLab Historian
• 2.3.2.5 Estimating $\alpha$
• 2.3.3 Matching the Model to Experimental Data
• 2.4.1.1 Read data into a Pandas DataFrame
• 3.9 Lab Assignment 4: Solution
• 4.1.2.1.4 Accessing Data using pandas
• 4.2.1 Output Feedback Control
• 5.2.3.1 Consolidating
• 5.4 Gasoline Blending
• 5.6.5 Display Composition
• 5.99.3 Example 19.3: Linear Programming Refinery
• 7.2.2 3.3.2 Example: A room full of Roombas
• 7.2.3 One Roomba
• 7.2.5 Adding the full complement of Roombas
• 7.2.6 Charging stations as shared resources
• 7.2.7 How many charging stations are required?
• 7.2.8 Adding a reporter process
• 7.4.4 Generating Customer Orders
• 7.4.4 Generating Customer Orders
• 7.4.5 Order Processor
• 7.4.5 Order Processor
• 7.4.5 Order Processor
• 7.4.7 Completed Model
• 7.5.6 Example: Simulation of an Order Processing Queue

pyomo

• 5.4 Gasoline Blending
• 5.4.3 Blending Model
• 5.6.4 Optimization Model
• 5.99.1 Pyomo Model

random

• 7.4.4 Generating Customer Orders
• 7.4.4 Generating Customer Orders
• 7.4.5 Order Processor
• 7.4.5 Order Processor
• 7.4.5 Order Processor
• 7.4.7 Completed Model
• 7.5.4 Simulating a Poisson Process in SimPy
• 7.5.6 Example: Simulation of an Order Processing Queue
• 7.5.7 Batch Processing Example (NEEDS REWORK))

seaborn

• A.1.3.1 Step 1. Create the background frame.
• A.1.4 Example: Phase Plane Animation for an Exothermic Stirred-Tank Reactor

simpy

• 7.1.1 Creating a simulation environment
• 7.1.2 Creating simulation processes
• 7.1.2 Creating simulation processes
• 7.1.3 Events
• 7.1.4 Ready to Roomba
• 7.1.4 Ready to Roomba
• 7.1.5 Chemotaxis
• 7.2.3 One Roomba
• 7.2.5 Adding the full complement of Roombas
• 7.2.6 Charging stations as shared resources
• 7.2.7 How many charging stations are required?
• 7.2.8 Adding a reporter process
• 7.3.1 Simulation with Simpy
• 7.4.4 Generating Customer Orders
• 7.4.4 Generating Customer Orders
• 7.4.5 Order Processor
• 7.4.5 Order Processor
• 7.4.5 Order Processor
• 7.4.7 Completed Model
• 7.5.4 Simulating a Poisson Process in SimPy
• 7.5.6 Example: Simulation of an Order Processing Queue
• 7.5.7 Batch Processing Example (NEEDS REWORK))

tclab

• 1.4.8 Running Diagnostics

time

• 1.4.3.2 Setting heater power with .Q1() and .Q2()-and-.Q2()`)
• 1.4.4 Synchronizing with Real Time using clock