A closed-loop feedback control system measures the actual…

A closed-loop feedback control system measures the actual state, computes the error against a setpoint, and actuates to reduce that error — continuously, automatically, and despite external disturbances. — Control theory

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What Jenco calls a desired state system is closed-loop feedback control applied to software: the sensor is state observation, the comparator is diff, the actuator is the API call. →

Locke and Latham explicitly cite cybernetic engineering as the source of their model — the same closed-loop feedback control behind Watt's governor and every thermostat. →

Empirical process control is closed-loop feedback control applied to work processes: execute is the actuator, inspection is the sensor, adaptation is the comparator adjusting the plan. →

In control theory this is the sensor — without measuring actual state, the loop is blind. CA's need to observe reality before acting is the same requirement every feedback controller has. →

In control theory this is called dead band — the comparator ignores errors below a threshold. Every physical controller has tolerance built in; CA must define one explicitly. →

Discrepancy Production vs Reduction The distinction between discrepancy reduction and discrepancy production is the central theoretical disagreement between control theory (Carver & Scheier, 1981) and goal-setting theory (Locke & Latham) regarding human motivation (bib). →

Empirical Process Control EPC is feedback control applied to work processes. The parallels are structural: a reference signal (sprint goal / product vision), a sensor (transparency), a comparator (inspection), and an effector (adaptation). What makes it "agile" is the short cycle time — the loop runs every sprint rather than every quarter (OKR) or every project phase (waterfall). →

GitOps for Fleet Management Self-healing through continuous reconciliation. GitOps continuously compares actual vs. desired state. Rollbacks are simple: revert the git commit. This is closed-loop feedback control applied to device management — the same pattern behind every thermostat and Watt's governor. →

Kanban Method Kanban maps cleanly to feedback control: →

Goal Setting and Task Motivation (Locke & Latham, 2002) The paper explicitly rejects pure feedback control as the basis for motivation. Locke & Latham argue that Carver and Scheier's (1981) control theory — a negative feedback loop modeled on the thermostat — treats discrepancy reduction as the source of motivation, implying that the natural state of the organism is rest. Instead, they adopt Bandura's (1989) position: goal-setting is primarily a discrepancy-creating process. People who attain a goal set a higher one, producing new gaps to master. The dual cycle is "disequilibratory discrepancy production followed by equilibratory reduction." →

Feedback Loops

Control Theory (Wikipedia) — overview of the field: Maxwell → PID → cybernetics → modern control (bib)
Open-Loop vs Closed-Loop Systems — the fundamental distinction: does the system re-check actual state?
Stability in Feedback Systems — overshoot, oscillation, settling time, steady-state error
PID Control — the canonical controller: proportional + integral + derivative
Controllability and Observability — prerequisites: can you steer it? can you see it?
Robustness in Control Systems — handling model imprecision and disturbance
2039567024205267136 — closed-loop feedback control: measure, compare, actuate
2039566010131558818 — Kubernetes reconciliation loop as a specific implementation
2039567945400254882 — Kubernetes' loop is Watt's governor (1788) applied to software
2039613059178873301 — dead band: the range where the controller deliberately does nothing

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OKRs: The Ultimate Guide (Atlassian) The user's xettel frames OKR as a 90-day feedback loop and a thermostat that checks once a season. The Atlassian guide confirms this: quarterly review is the recommended cadence. From a feedback control perspective, OKR is a closed loop with a very low sampling rate — the comparator fires once per quarter. →

OKR (Objectives and Key Results) From a control theory perspective, OKR is a closed-loop system with a quarterly sampling rate: the objective is the reference signal, key results are the sensor output, the quarterly review is the comparator, and team action is the effector. →

Open-Loop vs Closed-Loop Systems A closed-loop system continuously observes actual state and feeds the error back into the controller (xettel). An open-loop system acts without re-checking — it assumes its action was sufficient or that no external actor will change the state. →

Scrum Scrum's three pillars — transparency, inspection, adaptation — map directly to feedback control: →