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PythonLinearNonlinearControl
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Shunichi09 2020-04-07 20:45:10 +09:00
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Environments.md
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@ -39,7 +39,7 @@ R = diag[0.1, 0.1]
X_g denote the goal states.
## [CatpoleEnv (Swing up)]((PythonLinearNonlinearControl/envs/cartpole.py))
## [CatpoleEnv (Swing up)](PythonLinearNonlinearControl/envs/cartpole.py)
System equation.

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README.md
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# PythonLinearNonLinearControl
@ -116,21 +116,21 @@ It should be noted that **Model** and **Environment** are different. As mentione
<img src="assets/concept.png" width="500">
## Model
## [Model](PythonLinearNonlinearControl/models/)
System model. For an instance, in the case that a model is linear, this model should have a form, "x[k+1] = Ax[k] + Bu[k]".
If you use gradient based control method, you are preferred to implement the gradients of the model, other wise the controllers use numeric gradients.
## Planner
## [Planner](PythonLinearNonlinearControl/planners/)
Planner make the goal states.
## Controller
## [Controller](PythonLinearNonlinearControl/controllers/)
Controller calculate the optimal inputs by using the model by using the algorithms.
## Runner
## [Runner](PythonLinearNonlinearControl/runners/)
Runner runs the simulation.