casadi | symbolic framework for numeric optimization implementing | Math library

by casadi C++ Version: 3.6.5 License: LGPL-3.0

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | casadi Summary

casadi is a C++ library typically used in Utilities, Math applications. casadi has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has medium support. You can download it from GitHub.

Learn all about CasADi at the homepage or jump to install instructions...

Support

Quality

Security

License

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Support

casadi has a medium active ecosystem.

It has 1257 star(s) with 316 fork(s). There are 50 watchers for this library.

There were 3 major release(s) in the last 6 months.

There are 560 open issues and 2421 have been closed. On average issues are closed in 890 days. There are 12 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of casadi is 3.6.5

Quality

casadi has 0 bugs and 0 code smells.

Security

casadi has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

casadi code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

casadi is licensed under the LGPL-3.0 License. This license is Weak Copyleft.

Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

Reuse

casadi releases are available to install and integrate.

It has 31455 lines of code, 1510 functions and 146 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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casadi Key Features

No Key Features are available at this moment for casadi.

casadi Examples and Code Snippets

No Code Snippets are available at this moment for casadi.

Community Discussions

Trending Discussions on casadi

Integrate pre-compiled libraries into C++ codebase with CMake ExternalProject

How to discretize a nonlinear system

MPC for a mecanum wheeled model using Drake

Neural Network MPC

QUESTION

Integrate pre-compiled libraries into C++ codebase with CMake ExternalProject

Asked 2022-Mar-20 at 20:51

I want to integrate CasADi into a CMake-based C++ codebase as an ExternalProject. For this purpose, I would like to use pre-compiled libraries because building from source is not recommended. So far, I have only managed to write the following:

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ANSWER

Answered 2022-Mar-20 at 20:51

There is a natural problem with ExternalProject_Add:

ExternalProject_Add executes commands only on build.

Hence, download will not happen at the configure stage of your project which makes it difficult to use find_package, because the files cannot be found during your first configure run.

Take this CMakeLists.txt:

Source https://stackoverflow.com/questions/71489173

QUESTION

How to discretize a nonlinear system

Asked 2021-Oct-05 at 04:22

How can i discretize the following nonlinear system. Im using Matlab and Casadi for Model Predictive Control. The Constant C is betwenn 0 and 1.

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ANSWER

Answered 2021-Oct-02 at 12:23

If you are just looking to build it from blocks, something like this should work:

You basically need to invert the formula to:

Source https://stackoverflow.com/questions/69416635

QUESTION

MPC for a mecanum wheeled model using Drake

Asked 2021-Apr-26 at 17:58

I'm new to MIT Drake, I was using CasADi (ipopt) for a mecanum wheeled model for MPC.

In CasADi, I can create a symbolic variable for the optimization parameters (i.e., initial state and target state).

Then use it to compute the error in state, how can I get an equivalent functionality in Drake?

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ANSWER

Answered 2021-Apr-10 at 15:52

I've definitely seen mechanum wheels work in drake, but doing trajectory optimization for them requires some thought. For most every wheeled robot trajectory optimization, you want to use a minimal coordinates model. I discuss that briefly in the ballbot example in the notebook associated with http://underactuated.csail.mit.edu/acrobot.html

And for formulating your MPC, I would recommend the notes in http://underactuated.csail.mit.edu/trajopt.html

Source https://stackoverflow.com/questions/67035718

QUESTION

Neural Network MPC

Asked 2021-Jan-15 at 16:09

So I want to use Neural Network as my learned dynamic model function for MPC control in Python. I have not found any example/documention of doing this with open-source optimization packages like CASADI , GEKKO , do-mpc ? does any one have some reference/suggestion for achieving this? THANKS

Edit 01 a) I have tried CASADI + tensorflow model CASADI have a blog of how to use tensorflow model with CASADI. I am entirely not sure if I have done the implementation correctly as obviously I am not getting expected results. b) Upon looking on Internet there is "mpc. Pytorch" library which is a mpc toolbox which provides nn models as well. Not sure of its capability C) do-mpc which is based on CASADI is planning to integrate NN model. d) AS mentioned by @john gekko has the capability to use NN in mpc.

does any one know any other ways?

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ANSWER

Answered 2021-Jan-14 at 21:18

Here is an example with a Neural Network and MPC: TCLab G - Nonlinear MPC. A potentially better way is to use an LSTM to emulate control (PID or MPC) as shown in a series of articles in Towards Data Science. This approach is also the basis for many explicit MPC publications that use methods for storage and retrieval of the solutions. I published an article on this method that includes a case study with ISAT and a Neural Network.

Hedengren, J. D. and Edgar, T. F., Approximate Nonlinear Model Predictive Control with In Situ Adaptive Tabulation, Computers and Chemical Engineering, Volume 32, pp. 706-714, 2008. Preprint

Using a storage and retrieval approach, you don't need to solve the MPC application each cycle, only use the machine learned prediction that is trained based on prior MPC moves.

Source https://stackoverflow.com/questions/65720961

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install casadi

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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