Using LSTM network in Nonlinear MPC design?

23 次查看（过去 30 天）
Armin Norouzi
Armin Norouzi 2021-6-11
评论： MD RAHAT 2023-9-14
Hello everyone,
I would like to identify a system that has three inputs [u_1(k) u_2(k) y(k-1)] and single output as y(k) using LSTM time series estimation. I have a couple of questions regarding the implementation of this model in nonlinear MPC.
Based on the documentation of NMPC, I need to define a function for a state called StateFcn and an output called OutputFcn. As my model is based on the LSTM network, I was wondering how I can do that? Unfortunately, I couldn't find any example when I dig more into it. It worth mentioning that I am using GT-suit co-simulation as a virtual test machine, and I am going to implement this LSTM-based MPC to that.
Thank you in advance for your help.
  3 个评论
显示 1更早的评论
Dun-Ren Liu
Dun-Ren Liu 2022-12-26
I face the same problem.can you please share the solution?
thanks~
MD RAHAT
MD RAHAT 2023-9-14
I am having exactly same problem. Can you please guide me a little if you have found the solution to it

请先登录，再进行评论。

请先登录，再回答此问题。

回答（1 个）

Niccolò Dal Santo
Niccolò Dal Santo 2021-7-30
Hi Armin,
If I understand correctly you'd want train an LSTM for a time series with feedback. You can follow this example which shows how do that:
https://www.mathworks.com/help/deeplearning/ug/time-series-forecasting-using-deep-learning.html?lang=en
You should define your inputs as a three-elements vector ([u_1(k) u_2(k) y(k)], hence numFeatures = 3), one response and train your LSTM accordingly.
For further reading, here is an example for training an LSTM with more than one input feature: https://www.mathworks.com/help/deeplearning/ug/sequence-to-sequence-regression-using-deep-learning.html
Hope this helps.
Cheers,
Niccolò
  1 个评论
Armin Norouzi
Armin Norouzi 2021-8-17
Thank you for your response. I modeled my system using LSTM, and my main problem is how to use this model inside nlmpc mode. I understand that this model predicts sequence output for given sequence input. However, in nlmpc, I need to provide x(k+1) = f(u(k)) model, i.e., for given inputs in the previous time step, a model needs to be capable of estimating the next time step output. I would appreciate it if you could share your thoughts about this matter.

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Model Predictive Control Toolbox 的更多信息

标签

产品


版本

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by