What is the best way to implement my algorithm in Simulink ?

版本 1.4.0 (2.2 MB) 作者: Giampiero Campa
Eight ways to implement an Extended Kalman Filter as a Simulink block
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更新时间 2023/10/12

best-way-to-implement-an-algorithm-in-simulink

Eight ways to implement an Extended Kalman Filter as a Simulink® block

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This package contains some examples and a presentation (given at the International Conference on Robotics and Automation, Hong Kong, June 2014) discussing several possible ways of implementing an algorithm in Simulink.

Specifically, a simple Extended Kalman Filter based algorithm for attitude estimation is implemented in Simulink using S-functions (in C and MATLAB), System objects:tm:, S-Function Builder, Legacy Code Tool, and the MATLAB® function block (using both internal and external states).

Advantages and drawbacks of the different methods are discussed, and performance is then compared in several ways. First, the different models are simulated in Simulink, then, executable files generated from each models are executed both on an Intel laptop and on an Arduino Uno, with interesting results.

引用格式

Giampiero Campa (2024). What is the best way to implement my algorithm in Simulink ? (https://github.com/giampy1969/best-way-to-implement-an-algorithm-in-simulink/releases/tag/v1.4.0), GitHub. 检索来源 .

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版本 已发布 发行说明
1.4.0

See release notes for this release on GitHub: https://github.com/giampy1969/best-way-to-implement-an-algorithm-in-simulink/releases/tag/v1.4.0

1.3.0.0

Updated just a few slides.

1.1.0.1

Updated license

1.1.0.0

Streamlined signal generator
Included the Legacy Code Tool method in the final on-board embedded code comparison.

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要查看或报告此来自 GitHub 的附加功能中的问题,请访问其 GitHub 仓库