Do-mpc

Release notes
Please see the notes of release v4.6.3.

Minor changes

- The penalty term (`rterm`) of the MPC formulation can now be customized. For more information, see the [documentation](https://www.do-mpc.com/en/latest/api/do_mpc.controller.MPC.html#set-rterm)
- All CasADI integrator options can now be accessed via the `simulator.settings` syntax. For more information see the [documentation](https://www.do-mpc.com/en/latest/api/do_mpc.simulator.ContinousSimulatorSettings.html#do_mpc.simulator.ContinousSimulatorSettings)
- The `settings `attribute of the `MPC `and `Simulator `classes is now called `_settings`. It can be accessed via the `settings `method. The user interface remains identical.
- Minor bug fixes in the documentation an the `Simulator `class

Minor changes

- Added new settings attribute in `_mpc.py`
- Added citation file

Minor changes
- Fixed 387
- ``do-mpc`` can now be installed either as:

pip install do_mpc

or

pip install do_mpc[full]

Only with the full installation, optional features are available, e.g.:
- ONNX conversion
- OPCUA

Backend changes
- Fixed readthedosc configuration according to the new [specification](https://docs.readthedocs.io/en/stable/config-file/v2.html)
- New setup for requirement files (splitting the pip requirements files according to this [description](https://stackoverflow.com/questions/11704287/split-requirements-files-in-pip)):
- ``requirements.txt`` lists the base requirements for the do-mpc core features.
- ``requirements_full.txt`` is a superset of requirements and includes optional do-mpc features (e.g. ONNX conversion).
- ``requirements_docs.txt`` is a superset of the full requirements and includes the packages required to build the docs.

Major changes

For detailed information on the major changes, please visit our website [www.do-mpc.com](https://www.do-mpc.com/en/latest/).

OPC UA module
Building on the [opcua-asnycio](https://github.com/FreeOpcUa/opcua-asyncio) library, do-mpc now facilitates plant communication and software-in-the-loop testing with OPC UA.
- Core MPC modules can automatically derive and OPC UA client
- A local OPC UA server can be configured with namespace derived from clients for testing purposes


Interoperability with deep learning toolboxes through ONNX
``do-mpc`` now supports the open neural network exchange ([ONNX](https://onnx.ai)) standard.
- Incorporate neural networks previously trained in Tensorflow, Pytorch, Matlab, etc. (with an option to export ONNX models)
- Convert ONNX models to CasADi expressions (the backbone of ``do-mpc``).

Improved interface for settings in the MPC, MHE, Simulator, etc.
All do-mpc core modules now have the important new attribute ``settings``.
Previously, settings were passed to ``set_param``. This method is still available and wraps the new interface. The new method has important advantages:
1. The ``settings`` attribute can be printed to see the current configuration.
2. Context help is available in most IDEs (e.g. VS Code) to see the available settings, the type and a description.

Relaunch of documentation
We have significantly improved our documentation with a polished new look and included typing information for an improved workflow.

Please see the changes for v.4.5.0. This is a minor update to fix the installation routine of do-mpc.