# Adaptative-Predictive Control¶

This controller incorpores an algorithm for self-tuning i.e, the controller settings are ajusted automatically.

**PID Mathematical Model - Adaptative Predictive controller configuration**

The next table describes all the parameters available and what means each one of them.

Field |
Description |
---|---|

Enable Sys ID |
Activates the option of system identification. The plant is modified continuously by predicting a new one according to a set of parameters. This option must be activated when working in Adaptative – Predictive control. |

Noise Level |
Supposed noise level during System Identification |

Filtering Constant |
Constant value for the filter |

Initial A & Initial B |
Used to establish the initial plants constants for the system identification process |

Lambda |
Parameter that defines the control aggressiveness. High value means less aggressive control, low lambda means more aggressive control |

Optimal |
Select this option to use the Optimal AP algorithm |

f |
Sampling input period |

ro |
Control output period |

Enable/Disable Driver |
Mark this option to use the Driver Block |

TAU |
Time constant for the desired default trajectory |

In addiction, it is possible to display an AP panel in the workspace that allows the user to perform the following actions:

**Initial to Current:**to set the initial platform model to the current one.**Current to Initial:**to save the actual model to the initial one

**PID Mathematical Model - AP Tool in Workspace**