Hello
Based upon the calculations in the paper:
ROBUST NEURAL NETWORK CONTROL OF A QUADROTOR HELICOPTER
C. Nicol,C.J.B. Macnab, A. Ramirez-Serrano
An analytical simulator was coded in Mathematica 8.x for quadcopters:
http://www.wolfram.com/cdf-player/ you need to download this free player
All four motors are at 100%:
http://lossofgenerality.devzing.com/blog/2012/03/02/offline-training-data-for-quadcopter-1/
One motor is 4% less:
http://lossofgenerality.devzing.com/blog/2012/03/02/offline-training-data-for-quadcopter-2/
The quadcopter is fully specified with all the necessary mechanical and aerodynamic parameters. So the analytical calculations are true to the physical model of an actual quadcopter. They are not general for some abstract quadcopter, they are specific to a particular make and model.
I consider the analytical simulation quite primitive and has room for much improvement. The first derivatives are treated as moving averages of second derivative differentials. The time resolution is 1/1000 s, for 3 seconds of flight which is a take-off from the ground.
The output is a tabular ASCII file made from first and second partial derivatives of the Roll, Pitch, Yaw and X, Y, Z (with regards to time) and their corresponding values. The orientation of the copter in the interactive animation is true to the analytics.
Easily turbulence, noise and off-balance forces can be added.
These files can be used to test and train NN control systems for Arducopter.
Dara
Replies
Here a very interesting chip with Neural network chip with 1024 neurons in parallel. Access through parallel bus and I2C serial bus. Interface includes a digital input bus which can be connected optionally to a built-in recognition logic engine.
The CogniMem™ CM1K Chip is the first ASIC version of the CogniMem neural network product line optimized for Cognitive Computing. It features 1024 neurons working in parallel implementing two reknown non-linear classifiers. It can recognize patterns at high speed while coping with ill-defined data, unknown events and changes of contexts and working conditions.
More infos at: http://www.cognimem.com/products/chips-and-modules/CM1K-Chip/index....
Regards, Jean-Louis
Hello Dara,
Thanks for you info... I am currently developping a Neural Network Controller for the APM based on Adaptative Neural Networks, (no PID here), its begins to work, see below:
At this moment, I need to find how to get more heap space for the neural network memory, because the APM heap is full (8k only..)
Stay Tuned,
Regards, Jean-Louis