apgeorg/pid-control

PID Control

PID Controller

The objective of this project was to implement a PID controller in C++ to maneuver a vehicle around a track. The simulator provides the cross track error (CTE) and the velocity in order to compute the appropriate steering angle.

Propotional Term

The propotional term makes the current error signal multiplied with a gain (Kp) to get the controllers output. A small propotional gain Kp leads to the setpoint, but the controller performance will be slow. If Kp is increased, the controllers output overshoots.

Integral Term

The integral term makes the current error signal value and duration multiplied with a gain (Ki). In addition, when the integral term is added to the propotional term, it accelerates the movement of the process towards setpoint and eliminates the residual steady-state error that occurs with a propotional only controller.

Derivative Term

The derivative term makes the rate of change of the error signal multiplied with a gain (Kd). Further, it slows the rate of change of the controller output and this effect is most noticeable close to the controller setpoint.

Tuning PID Hyperparameters

The PID hyperparameters were tuned experimentally with the algorithm shown below[1] in order to control the steering angle based on the CTE while watching the effect on the behaviour of the car driving around the track.:

• Set all gains to 0.
• Increase Kd until the system oscillates.
• Reduce Kd by a factor of 2-4.
• Set Kp to about 1% of Kd.
• Increase Kp until oscillations start.
• Decrease Kp by a factor of 2-4.
• Set Ki to about 1% of Kp.
• Increase Ki until oscillations start.
• Decrease Ki by a factor of 2-4.

References

[1] https://robotics.stackexchange.com/questions/167/what-are-good-strategies-for-tuning-pid-loops