controller gain and tuning
A controller's gain is simply how hard it pushes back when something is off. Imagine steering a car back into your lane: if you barely turn the wheel, you drift for ages before you straighten out; if you yank it hard, you overshoot to the other side and start weaving. The gain is that turn-the-wheel-how-much choice, written as a number the controller multiplies the error by. A small gain reacts gently and slowly; a large gain reacts fast and forcefully. Tuning is the hands-on craft of picking those numbers so the machine corrects itself quickly without overshooting, shaking, or going unstable.
Most real controllers have not one knob but several — for example the three terms of a PID controller, each with its own gain — and they pull against each other. Crank one up for speed and you often pay in wobble; calm the wobble and the response gets sluggish. So tuning is always a balancing act between three things people care about: responsiveness (how fast it reaches the target), stability (whether it settles instead of oscillating forever), and overshoot (how far it sails past the target before settling). Good tuning finds the sweet spot where the system is brisk, calm, and steady all at once.
Engineers tune in different ways. Some turn the knobs by hand and watch how the machine behaves, nudging each gain up or down until it feels right. Others follow recipes — step-by-step rules of thumb that suggest starting values from a quick experiment. And many modern systems tune themselves, measuring their own response and adjusting the gains automatically. Whatever the method, the goal is the same: numbers that make the controller push back by just the right amount — not too timidly, not too violently.
A drone with its altitude gain set too high bounces up and down past its target height before settling; turn that gain down a notch and it glides smoothly to the right height and holds.
Same drone, two gain settings: too high bounces, just right settles.
There is no single correct gain — the right values depend on the machine, the task, and even the load it carries, which is why tuning is often redone when conditions change.