1. Limited time only! Sign up for a free 30min personal tutor trial with Chegg Tutors
    Dismiss Notice
Dismiss Notice
Join Physics Forums Today!
The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

Neural network controller for internal combustion engine

  1. Apr 15, 2010 #1
    I'm currently doing a project on neural network controller for an internal combustion engine to reduce emissions level. Can anyone assist me in training such models (neural networks)
     
  2. jcsd
  3. Apr 18, 2010 #2

    Mech_Engineer

    User Avatar
    Science Advisor
    Gold Member

    What's the advantage of using a neural network in this situation? It seems to me a standard PID loop is perfectly sufficient...
     
  4. Apr 18, 2010 #3
    Perhaps a neural network can be trained to optimize PID gains.
     
  5. Apr 18, 2010 #4

    russ_watters

    User Avatar

    Staff: Mentor

    Most halfway decent PID controllers are self-tuing. Your car already does this.
     
  6. Apr 18, 2010 #5
    Cars are self-tuning, how do they do this?
     
  7. Apr 18, 2010 #6

    russ_watters

    User Avatar

    Staff: Mentor

    For starters, by keeping track of operating parameters and matching the next one to the previously logged parameters. How much further it goes beyond that, I'm not sure, but a home thermostat does similar things. It keeps track of overshoot and adjusts the timings to compensate.
    http://en.wikipedia.org/wiki/Programmable_thermostat

    I'm not sure exactly how much a car's computer does, but if you've ever run the battery completely dead on your car, you may notice that it has trouble idling for a while until it figures out how to properly control the fuel/air mixture.
     
  8. Apr 18, 2010 #7
    Mmmm.....I don't believe this explanation. A PID controller has a set of gains which are determined based on a linear model of the system.

    All you have described is how the PID controller works, not how the controller figures out which gains to use. Perhaps they are doing gain scheduling where the map a series of gains based on the closest conditions of the system at the time, but none of these explanations talk about how it (if at all) 'figures out' what gains to use.
     
  9. Apr 18, 2010 #8

    D H

    User Avatar
    Staff Emeritus
    Science Advisor

    I hope you guys do know that you aren't helping the OP one iota. And you haven't rolled out the welcome mat, either! Bad form!

    That said, this is not a good opening post:
    So, first off, rolling out the official welcome mat: Welcome to PhysicsForums, Jaco!

    Now I'm going to pick on you a bit, Jaco. Don't take it too personally. Hopefully this will help other newbies learn to phrase things a bit better (and you too, Jaco; this can be a very helpful place).

    We do have some written rules here; you violated an unwritten one. A very big one, too. The rule is don't ask us to write a book. That is precisely what you have done by asking us "Can anyone assist me in training such models (neural networks)". The question is too open ended, too vague. The answer would require us to write a book on neural nets. There are in fact many books whose main topic is this very question.

    So, Jaco, if you are still around, I'll help you in terms of questions. First question, very important:

    What research have you done on this topic? We are a lot more willing to help students who have shown some work of their own.

    Now some more questions that you should investigate during your research:
    • Why would someone want to use neural nets when conventional control theory does a bang-up job for the most part?
    • Where does conventional control theory start to unravel?
    • Are neural nets already in use in the auto industry? By whom?
     
Know someone interested in this topic? Share this thread via Reddit, Google+, Twitter, or Facebook




Similar Discussions: Neural network controller for internal combustion engine
Loading...