control

Control is the engineering of behavior over time: measure a system, compare it with a desired state, and choose inputs that keep the error bounded despite disturbances and imperfect models. Where systems theory describes the dynamics of interconnected systems, control asks how feedback changes them; robotics is one of its largest users, every robot closing loops through sensors, computation and actuators.

Control is the engineering of behavior over time: measure a system, compare it with a desired state, and choose inputs that keep the error bounded despite disturbances and imperfect models. Where systems theory describes the dynamics of interconnected systems, control asks how feedback changes them; robotics is one of its largest users, every robot closing loops through sensors, computation and actuators.

Feedback buys robustness by reacting to reality instead of trusting the model. It also creates the possibility of oscillation and instability.

A controller cannot repair missing authority. Sensor delay, actuator saturation, noise, and plant dynamics set physical limits before tuning begins.

The plant, the controller and the closed loop are separated in feedback control; which modes inputs can reach and sensors can see is controllability and observability; vertical drone runs both on one axis.

The PID controller is popular because proportional, accumulated, and anticipatory error cover a remarkable amount of industry with little computation. State-space methods expose more structure when variables interact strongly.

A practical loop is drawn part by part in control loop; it is judged by its step response and by the margins of its frequency response.