Aeronautical Systems - Guidance and Control
Last updated: 03/18/2015
Author Information
Professor Franco Bernelli
Politecnico di Milano
Aureliano Rivolta
Politecnico di Milano
Dario Cuzzocrea
Politecnico di Milano
Course Details
Description
This course was first held in Politecnico di Milano during April and July 2014, with the goal of teaching a practical approach to engineering. The lessons and models provide students both theoretical and practical tools to help them learn control theory and model based design. They will learn kinematics and dynamics and develop the equations of motion for a blimp. Using Simulink, they will model the dynamics of the blimp and design PID controllers for both altitude and yaw control. Using the Simulink Hardware Support Packge for Arduino and a custom Simulink toolbox developed specifically for this course, the students will deploy their controller designs to Arduino hardware.
In the first three lessons students are introduced to MATLAB, the non-linear six degree of freedom equations of motion are developed and used to describe the motion of the blimp, and the use of state space and linear transfer function models for calculating the frequency response of dynamic systems is demonstrated. In the fourth lesson, Simulink is used to model the dynamics of the blimp and examples of PID controllers are given. Students will learn to program an Arduino board to control the blimp using Simulink in the fifth lesson and Kalman filters are introduced in the final lesson to develop navigation equations for the blimp.
Figure 1: The blimp built for the course.
CAD models of the blimp and circuit design files for an Arduino sensor shield are packaged with the material for this course to allow the students to build a copy of the blimp used in the course.
Original Course Documents
BLIMP 2014
Course Contents
- Getting Started
- Examples
- Language Fundamentals
- Mathematics
- Graphics
- Programming
- Reference Frames
- Inertial Reference Frame
- NED Reference Frame
- Body Fixed Reference Frame
- Coordinate Systems
- Law of Dynamics
- Center of Mass
- Linear Momentum Conservation
- Angular Momentum Conservation
- Kinematics
- Direction Cosine Matrix
- Euler Angles
- Quaternions
- Linear Systems and State Space Representation
- State of a Dynamic System
- The State Equation
- Output Equations
- State Equation Based Modeling Procedure
- Transformation From State-Space Equations to Classical form
- Transformation From Classical Form to State-Space Representation
- The Matrix Transfer Function
- Frequency Response
- The Concept of Frequency Response
- Analytical Expressions for the Frequency Response
- Introduction
- Simulink
- Getting Started
- Most Important Blocks
- Pulse Response
- Blimp System's Stability
- Altitude Stability
- Yaw Stability
- Direct Integration
- What is Arduino
- Programming Arduino with Simulink
- A First Example
- Traffic Light Controller
- Servo Control
- Sensors Reading with Simulink and Arduino
- What is a MEMs
- MEMs Communication Interface
- Skyward Blimp Target
- Read Data from Sensors
- PID Example
- Principles of Navigation
- Determining Attitude
- Determining Position
- Random Process (basics)
- Linear Systems: Observer
- Observability
- Observer Derivation
- Kalman Filter
- Kalman filtering
- Recursive Kalman Filter
- Extended Kalman Filter
- Optimal Control
- Blimp Navigation
- Sensors
- Choice of Sensors
- Inertial Navigation System
- Altimeter
- Ranging Sensor
Course Materials
PID Simulators - Lesson 4
Arduino Examples - Lesson 5
Resources
Arduino Shield Circuit Diagram
Blimp CAD Models
Links
Skyward Experimental Rocketry
