Multi objective parameter estimation

[wilsonrljr]

SysIdentPy is a Python library that provides a wide range of tools for modeling and analyzing complex systems. One of the key features of SysIdentPy is its ability to perform parameter estimation using different methods. Currently, SysIdentPy supports several methods for parameter estimation, including least squares based techniques and adaptive filters methods. These methods are mono objective techniques, meaning that they focus on optimizing a single objective, typically the error of the dynamic model. However, in many real-world scenarios, it is often necessary to consider multiple objectives when modeling complex systems.

To address this issue, the SysIdentPy development team has set a goal to implement a multi-objective technique that will allow users to create models that are good for both dynamic and static behavior. This technique will enable users to add more than one objective to the model, which will result in a model that is more representative of the real-world system.

Multi-objective optimization is an important research area in the field of parameter estimation, and there are several popular techniques available, including the Pareto optimization and multi-objective genetic algorithms. By implementing a multi-objective technique in SysIdentPy, users will be able to take advantage of these advanced methods to create more accurate and reliable models.

To ensure the success of this project, the SysIdentPy development team will work closely with the developer that will implement the new method, which will be designed to be easy to use and accessible to a wide range of users, from beginners to advanced users.

The implementation of a multi-objective technique in SysIdentPy will provide users with a powerful new tool for modeling complex data. By allowing users to consider multiple objectives when creating a model, SysIdentPy will enable them to create models that are more representative of the real-world system and better able to capture both dynamic and static behavior.

In conclusion, the implementation of a multi-objective technique in SysIdentPy is an important step forward for the library and will provide users with a powerful new tool for modeling dynamical systems. With the support of the SysIdentPy development team, users can expect to have access to this new feature in the near future.

[GabrielBuenoLeandro]

I'd like to work on this feature. Thanks!

[wilsonrljr]

Added in v0.3.3

[samirmartins]

Wilson, please remove user "milanimartins" and add "samirmartins" instead. Thank you.