What Is Model Reference Adaptive Control (MRAC)? | Learning-Based Control, Part 3
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- Опубліковано 21 лип 2024
- Use an adaptive control method called model reference adaptive control (MRAC). This controller can adapt in real time to variations and uncertainty in the system that is being controlled.
See how model reference adaptive control cancels out the unmodelled dynamics so that a nominal plant model matches with a reference model.
A MATLAB® example shows where this adaptive control method is used to control the unknown and undesired rolling oscillations, which can occur in a delta-wing aircraft.
- Simulink Control Design: bit.ly/3709JTF
- Below references are displayed in a journey on Resourcium: bit.ly/3VTG57z
- MRAC controller: bit.ly/44UjkV1
- MRAC wing rock example: bit.ly/38KCtAq
- MRAC satellite spin example: bit.ly/3I3ZDQY
- Model Reference Adaptive Control Fundamentals (Dr. Tansel Yucelen): • Model Reference Adapti...
- Model Reference Adaptive Control Part-1 (Dr. Shubhendu Bhasin): • Model Reference Adapti...
- Adaptive Control (Part 1) - Hypersonics and the MIT Rule (Rodríguez): bit.ly/3I5QGX8
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I looked at a lot of resources to understand MRAC. Finally a video that breaks down the basics. Thanks a ton Brian! :)
I actually appreciate the effort that has been done in this video
Wow, I was looking for this exact kind of introduction to adaptive control, and find this video just uploaded today!
that was awesome! such a great topic. i immediately go in simulink to implement MRAC into some projects
Amazing!!! Thanks for such excellent explanation.
So those parameters could for example be estimated with for example least mean squares or recursive least squares? I assume that there should then also be some persistence of excitation condition in order to guarantee convergence, so would this then also require some sort of dithering to ensure this?
Hi Brian ! Thanks for this great video ! Could you add the link to the ressources about Lyapunov and MIT rules you mentionned please ? It would be greatly appreciated.
@brian im also interested
Me too
Hi can you please link to the videos you mentioned about the lyaponov rule? thanks for a great video
This video is amazing!
Awesome video !!! Love them all
awesome, pls more on this topic
awesome, thanks for this explanation, pls video for model predictive control
Thank you for this amazing video
excelllent lecture sir thank you so much
Very Nice, what video equipment are you using to build these videos. Also, you have infographics as well. Adaptive controls can be a lifetime of learning and getting this right. practicing with models most companies don't support. All these models and controllers need to be exercised. If you spend too much time modeling, the boss feels that you are not doing your job, but this is far from the truth. Most bosses have MSEE degrees or better but stay lost in meetings. They don't practice anything. It's hard to stay current using company time. Any ideas on how to create more time?
This is fascinating
Hi, Brian your videos about control theory is great , I hope you will talk about MPC controller :)
Excellent
Good video. Thanks
Thanks for the video, but I cannot see the resources on MIT rule and Lyapunov in the description!
good one.
I wonder how related is this to SMC since it also uses Lyapunov stability criteria to cancel unknown non linear behaviors
Thank you Brain for the nice explanation. Links to resources are not in the description.
Thanks for letting me know. I'm not sure why they got left off. I also put all of them in this Resourcium journey: resourcium.org/journey/companion-resources-adaptive-control-basics-what-model-reference-adaptive-control
so basically MRAC is to create a hallucination for control engineers that "this nonlinear systems follow a super simple linear model and I verified it in experiment!"
Hi Everyone, How can I improve the Iterative Learning Control Model Predictive Controller to enhance Atomic Force Microscopy performance?
which subject is this i was searching feedforward control system in physiology
Hi, why the uncertainty f(x) assumed to be appear with u(t) as B(u + f(x)), rather than \dot x = Ax + Bu + f(x)?
i need exampele with MRAC
Litterly creative concept and nicely explained 👍👍
Thanks!!
Imagine this bullshit happening to you and spending years in hell wondering what's wrong with you