> For the complete documentation index, see [llms.txt](https://docs.seattlesolvers.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.seattlesolvers.com/features/controllers/squidf.md).

# SquIDF

package com.seattlesolvers.solverslib.controller

A `SquIDF` controller is a variation of the `PIDF` controller that square roots the positional error term. Effectively, it extends the `PIDF` class, and overrides the `calculateOutput` method. This modification changes how the controller responds to errors of different magnitudes.

#### Key Differences from PIDF

| Aspect                    | PIDF                        | SquIDF               |
| ------------------------- | --------------------------- | -------------------- |
| **Proportional Response** | Linear with error           | Square root of error |
| **Large Errors**          | Stronger correction         | Moderate correction  |
| **Small Errors**          | Generally weaker correction | Stronger correction  |
| **Response Curve**        | Straight line               | Curved (sub-linear)  |

`SquIDF` helps reduces overshoot (since the square root dampens aggressive corrections when initial error is high), and generally gives a smoother approach. However, like a PID/PIDF, tuning is critical. The controller is only as good as you can tune it.

#### Usage Example

```java
// Create SquIDF controller with same gains as PIDF
SquIDFController squidfController = new SquIDFController(
    1.0,  // kP
    0.1,  // kI
    0.05, // kD
    0.2   // kF
);

// Use just like a PIDF controller
squidfController.setSetPoint(targetPosition);
double output = squidfController.calculate(currentPosition);
```

#### Tuning Notes

* **kP values** will typically need to be **higher** than in PIDF since √(e) < e for errors > 1
* Start with your PIDF gains and increase kP gradually
* The I, D, and F terms work pretty much identically to PIDF


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