date.chinmay
- 10
- 0
I'm working on a project which deals with temperature control of a room. the idea is to control temperature within a limit.
I have prior data which i used to train a neural network which is 99.5% accurate. there are 5 inputs (x , y , z , A , B) and there is one output (T).
Now I want to use this network in a control architecture of some kind. Any suggestions? which should I use?
P.S. The system is highly complex, non linear and dynamic in nature. I have already tried standard inversion of system but it doesn't work as outputs are lesser than inputs.
I'm doing this in Matlab.
I have prior data which i used to train a neural network which is 99.5% accurate. there are 5 inputs (x , y , z , A , B) and there is one output (T).
Now I want to use this network in a control architecture of some kind. Any suggestions? which should I use?
P.S. The system is highly complex, non linear and dynamic in nature. I have already tried standard inversion of system but it doesn't work as outputs are lesser than inputs.
I'm doing this in Matlab.