Implementation of simple PID control

Dependencies

• cmake >= 3.5
• All OSes: click here for installation instructions
• make >= 4.1(mac, linux), 3.81(Windows)
  • Linux: make is installed by default on most Linux distros
  • Mac: install Xcode command line tools to get make
  • Windows: Click here for installation instructions
• gcc/g++ >= 5.4
  • Linux: gcc / g++ is installed by default on most Linux distros
  • Mac: same deal as make - [install Xcode command line tools]((https://developer.apple.com/xcode/features/)
  • Windows: recommend using MinGW
• uWebSockets
  • Run either ./install-mac.sh or ./install-ubuntu.sh.
  • If you install from source, checkout to commit e94b6e1, i.e.

    git clone https://github.com/uWebSockets/uWebSockets 
    cd uWebSockets
    git checkout e94b6e1
    

    Some function signatures have changed in v0.14.x. See this PR for more details.
• Simulator. You can download these from the project intro page in the classroom.

There's an experimental patch for windows in this PR

Basic Build Instructions

1. Clone this repo.
2. Make a build directory: mkdir build && cd build
3. Compile: cmake .. && make
4. Run it: ./pid.

Tips for setting up your environment can be found here

Implementation

The implementation of the PID controller was straight forward, the function void PID::UpdateError(double cte) takes the current control error for calcuating the internal error gains and the function double PID::TotalError() returns the resulting control error value.

One instance of the PID class controls the steering, where the cross-tack-error (CTE) is being used as error value and the other PID instance controls the speed of the car by using the a target speed range between 10 and 40 mph, depending on the steering output, increasing speed at lower steering angles and decreasing for high steering angles, just like this: target_speed = 30. * (1. - abs(steer_value)) + 10.

For tuning the PID gains I started out with 0.1, 0.0005, 1.0 (P,I,D) and refined the parameters manually to 0.07, 0.002, 1.7. Good guidelines on how to tune PID parameters are:

• https://en.wikipedia.org/wiki/Controller_(control_theory)
• https://www.embedded.com/design/prototyping-and-development/4211211/PID-without-a-PhD

After manually tuning the PID parameters I implemented twiddle (used in class) in order to optimize the PID parameters in respect to the RMSE over a lap on the racing course.

Even after tuning the PID parameters carefully the car drives safe but very shacky, presumably a real passenger would throw up after only one lap already! I'm already curious on how model predictive control improves this situation ;)