Skip to content

Latest commit

 

History

History
47 lines (27 loc) · 878 Bytes

readme.md

File metadata and controls

47 lines (27 loc) · 878 Bytes

Controller Optimization Using Deep Learning

Deep learning for controller optimization.

Click for Youtube video:

Prereq.s

Tensorflow

python libraries:

chmod +x pythonReady.sh
yes "yes" | sudo sh pythonReady.sh

run

python main.py

ToDo

  • Implement NN in Propeller
  • Try RNN
  • Try Q-Learning to optimize the controller performance

Problem Setup

Stage 1: Show NN can perform PID less than equal to the performance of PID controller.
Stage 2: Show Q-learning can optimize NN structure.

Results

MSE = 1.6

Red: Actual PID output for ESC signal
Blue: NN output for ESC signal