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101 changes: 101 additions & 0 deletions Docs/3_Specifics/3.6_GainsTuning.md
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# Understanding PID and Feedforward Control

In the [controls article](3.1_ControlsIntro.md), we introduced feedback and feedforward control and explained why combining them is useful for tuning FRC mechanisms. Now, we need to understand how to actually use these constants in our control systems.

### There are two main groups of constants to understand

The feedforward gains include:
- kS - static friction
- kV - velocity
- kA - acceleration
- kG - gravity

The feedback gains include:
- kP - proportional
- kI - integral
- kD - derivative

Feedforward is proactive. We predict how much motor output is needed and apply that output immediately.

Feedback is reactive. the controller looks at what the mechanism is actually doing, compares it to the desired outcome, and corrects the error.

## Feedforward constants:

kS is static friction. kS represents the amount of motor output required to overcome static friction and get the mechanism to move.

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Same for all of these: maybe reword this to "kS is the static friction feedforward gain" or something to make it more clear what exactly the number refers to (like its not referring to the actual force of friction on the mechanism)

- if kS is too low the mechanism may not actually move or not move as much as it should because it's not outputting enough to overcome static friction
- if kS is too high the mechanism can jump when it starts moving because the output is more than necessary for overcoming static friction
- kS is particularly important for mechanisms with significant friction including arms, elevators, and some other gear-driven mechanisms

kV is velocity. kV represents how much motor output is required to maintain a particular velocity. As a mechanism moves faster it will require more motor voltage to maintain that speed and kV shows that relationship.
- kV is important for any mechanism where we care about controlling velocity.

kA is acceleration. kA represents how much additional motor output is needed to accelerate the mechanism. A mechanism that is already moving at a constant velocity does not need as much output as a mechanism that is rapidly trying to speed up for example, an elevator moving upward at a constant velocity needs enough output to overcome gravity while maintaining its speed so if we want it to accelerate upward we need more output which is represented by kA.
- not all mechanisms need kA but important for some

kG is gravity. kG represents the amount of motor output required to counteract gravity.
- only really useful when gravity actually affects a mechanism like an elevator or arms need it to account for the constant downward force exerted on it by gravity (i.e not things like rollers).

## Feedback constants
kP is proportional. kP is based on the current error. if the mechanism is far away from its target the controller will apply a large correction and if its close it will apply a smaller correction.
- if kP is too low the mechanism responds slowly and can't keep up with the target accurately
- if kP is too high the mechanism may overshoot, oscillate, or become unstable

kI is based on the accumulated error over time. An integral is the area under a curve or in our case the error accumulated over time so if error gradually builds up in our system I can help with that.

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I would make the connection between kI, integrals, and accumulated error over time more clear.

- kI is often not needed and will be set to 0 or a very small value in most cases. This is because kP and kD are often good enough. If kI is too high it can cause overshooting.

kD is based on how quickly the error is changing, it is looking at the rate of change of the error or how quickly it's approaching the target.

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This should be 2 sentences

- low kD can make the mechanism overshoot or oscillate.
- high kD can make the mechanism too slow to react or react excessively.

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Maybe this is what you mean by "react excessively" but the most common symptom of high kD is very rapid, almost spasm-like oscillations when near the setpoint


## Tuning Process

Understanding these things conceptually is the first step, but now we will include a guide on tuning for practical use. In general, you should not tune everything at once. A solid approach is making feedforward reasonably accurate, then using feedback to reduce the rest of the error. The process and constants you will need depends on the mechanism because they all have different physics. The procedure can depend on the motor controller, control mode, and mechanism. For example, it's important to distinguish between velocity and position control. If you're tuning a roller to maintain a certain RPM then you're dealing with velocity. However, if you're dealing with an elevator that needs to move to particular heights that's position control.

In general, the order for tuning is: kS, kV, kA, kG, kP, kD, kI (note: not all may be needed)

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We usually tune kG right after/along with kS


### Elevator tuning:

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Add kG tuning here. Usually, when tuning manually, I measure the voltage required to start moving up, representing (kS+kG), then the voltage required to start moving down (kS-kG). Then solve the system to get the correct gains

tune kS
- determine how much output is necessary to overcome static friction and get the elevator moving. The voltage when the mechanism just starts moving is approximately kS.

tune kV
- determine the kV by entering different velocities and determining how much kV is needed to maintain those.

tune kA

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I'm not really sure how to tune kA tbh, we usually just SysID it

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So maybe add a note that its not usually needed for hand-tuned mechanisms

- depends on how quickly we need the mechanism to accelerate, try increasing kA until it works

tune kG

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This does work for kG, however if you're tuning like this kG needs to come before kS to get an accurate static friction measurement. Otherwise kS will include kG

- increase kG until it counteract gravity (i.e enough to hold its position, not fall or rise when its supposed to hold still).

tune kP
- increase kP until elevator reaches target quickly and accurately, it its overshooting or oscillating its probably too high.

tune kD
- if the elevator overshoots or oscillates as it approaches the target adding kD may help. You can tune it by increasing it until the elevator settles smoothly without becoming excessively sluggish.

tune kI
- kI may not be necessarily but if there's consistently small position error it may help.

### Arm tuning:
similar to elevator processes with kS, kV, kA if necessary, kG(when arm is horizontal), kP, kD, and kI is necessary

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i think this should say "kI if necessary"

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Also once again kG should be tuned either along with kS or before it


### roller tuning:
typical rollers only need kS, kV, kA, kP, and kD

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Maybe note that kP and kD are usually very small (like on the order of 0.1 kP and 0.01 kD) if the feedforward has been properly tuned


## Additional tips:
- using tools such as SysID (see sysId article) rather than this process can give you kS, kV, and kA

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sysid also gives kG

- your tuning process and gains need to make sense for the control system your using whether that position, velocity, voltage, etc

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I would edit this sentence to be more clear. Also, you shouldn't need gains for voltage. I would also add that if you're planning to motion-profile a mechanism its PID should be tuned with a motion profile

- many motor controllers support control slots allowing you to store and select different gains this may be helpful for situations where there is not one perfect set of gains for every situation (such as carrying a game piece vs not carrying a game piece)

### Resources

- [WPILib Intro to PID](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/introduction/introduction-to-pid.html)
- [WPILib PID Control](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/controllers/pidcontroller.html)
- [WPILib PIDController](https://github.wpilib.org/allwpilib/docs/release/java/edu/wpi/first/math/controller/PIDController.html)








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