Process-Control

Process-Control #

Process-control (aka feedback-control) style is suitable when the system’s purpose is to maintain certain properties of a process output near a desired reference value (set point), despite disturbances.

Topology #

Example component diagram:

Feedback control loop topology

  • Component
    • Controller: computes actions based on the set point and feedback.
    • Processor: the (physical or software) component being controlled; it usually comes with some observers/sensors to collect telemetry data as feedback.

Pros and cons #

  • Pros
    • Robustness: can adapt to changing conditions and keep the system within acceptable bounds.
    • Autonomy: supports self-correcting behaviors (within designed limits).
  • Cons
    • Cost and complexity: requires monitoring/telemetry, calibration, and control logic.
    • Sensitive to latency: delayed or noisy feedback can cause oscillations/instability.

Real-world examples #

Autonomous driving #

Many components in an autonomous driving system are built around the process-control style. Consider steering: given a desired steering angle to follow a trajectory (set point), the system (controller) computes the torque command needed to reach that angle and send it to the vehicle’s steering actuator (processor); a sensor continuously reports the actual angle (feedback) back to the controller, which can be different than the desired angle because of road conditions, so that the controller can adjust the torque command accordingly. The same style applies to other components like throttle and braking.

Further reading: openpilot, Apollo (Baidu’s open-source autonomous driving platform).

TCP congestion control #

When a computer sends data over the internet, it needs to figure out how fast it can go without overwhelming the network. TCP congestion control does this with a feedback loop: the sender starts by transmitting slowly, then gradually speeds up. Each time the receiver acknowledges a batch of data, the sender treats that as a signal that the network can handle more and sends a little faster. If packets start getting dropped (a sign of congestion), the sender slows down. This is an example of the process-control topology: the set point is “send as fast as possible without causing congestion,” the controller is the algorithm that decides how much data to send next, the processor is the network, and the feedback is whether packets are arriving successfully. It also illustrates the stability trade-off: if the sender speeds up too aggressively it causes congestion, but if it backs off too cautiously it wastes available bandwidth.

Further reading: BBR: Congestion-Based Congestion Control, CUBIC TCP