# System and Controls Library
Collection of various tools in the field of systems and controls.
> Systems can mean just about anything.
> Here, we are talking about **dynamic systems**
> and how to find the **right input**
> to achieve a desired **state of equilibrium**.
As a first step, the library implements the **base controller class**
that defines the basic requirements for any **discrete-time** controller.
The **next step** is to derive **model-based** controllers
and then also **data-driven** controllers.
_At some point, the fundamentals of control systems such as PID could be integrated,
presumably as wrappers for existing libraries and tools._
## Usage
```python
from sysco import Controller # Controller subclasses not already implemented
# custom controller example
class MyController(Controller):
def get_input(self):
return 1
# instantiate custom class and get input
my_controller = MyController()
print(my_controller.get_input()) # --> 1
# try to instantiate base class
base_controller = Controller()
next_input = base_controller.get_input() # --> NotImplementedError
```
## Future development
To avoid bottlenecks later on, Rust is already built into the structure
## Controller (in planning)
### LQR
- First one that will be implemented
- Infinite horizon without constraints
Returns optimal input $u^\star$ that drives the System to the origin.
### MPC
#### Nominal Case
#### Economic MPC
#### Tracking MPC
#### Robust MPC
### Data-driven approaches
#### DeePC
#### RL-based
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"description": "# System and Controls Library\n\nCollection of various tools in the field of systems and controls.\n\n> Systems can mean just about anything.\n> Here, we are talking about **dynamic systems**\n> and how to find the **right input**\n> to achieve a desired **state of equilibrium**.\n\nAs a first step, the library implements the **base controller class**\nthat defines the basic requirements for any **discrete-time** controller.\n\nThe **next step** is to derive **model-based** controllers\nand then also **data-driven** controllers.\n\n_At some point, the fundamentals of control systems such as PID could be integrated,\npresumably as wrappers for existing libraries and tools._\n\n## Usage\n\n```python\nfrom sysco import Controller # Controller subclasses not already implemented\n\n# custom controller example\nclass MyController(Controller):\n def get_input(self):\n return 1\n\n# instantiate custom class and get input\nmy_controller = MyController()\nprint(my_controller.get_input()) # --> 1\n\n# try to instantiate base class\nbase_controller = Controller()\nnext_input = base_controller.get_input() # --> NotImplementedError\n```\n\n## Future development\n\nTo avoid bottlenecks later on, Rust is already built into the structure \ue7a8\n\n## Controller (in planning)\n\n### LQR\n\n- First one that will be implemented\n- Infinite horizon without constraints\n\nReturns optimal input $u^\\star$ that drives the System to the origin.\n\n### MPC\n\n#### Nominal Case\n\n#### Economic MPC\n\n#### Tracking MPC\n\n#### Robust MPC\n\n### Data-driven approaches\n\n#### DeePC\n\n#### RL-based\n\n",
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