# Python Control Design

> Use when designing and validating feedback control laws with Python control-systems tooling: evaluate gain and phase margins against acceptance limits (6 dB and 45 degrees), classify closed-loop stability from the margins, and apply Ziegler-Nichols tuning to get initial PID gains. Supports controller sanity checks (positive proportional, non-negative integral and derivative gains) before simulation or root-locus and Bode iteration. Pairs with the ARP4754A development-assurance context for control law development. Trigger: control law, pid, transfer function, state space, gain margin, phase margin, root locus, bode, stability, controller tuning.

- Skill: `ashfordeou/python-control-design` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add ashfordeou/python-control-design`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ashfordeou/python-control-design/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: Apache-2.0
- Author: ashfordeOU (https://skillmd.com/u/ashfordeou)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ashfordeou/python-control-design

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# Python Control Design (gnc-autonomy/control/python-control-design)

Use when the task is control law design and evaluation with Python
control-systems tooling: margin checks, stability classification,
and PID tuning.

## Domain quick reference

- Standard acceptance margins: gain margin >= 6 dB, phase margin
  >= 45 degrees.
- A loop with both margins positive is closed-loop stable; a
  non-positive margin indicates instability.
- Ziegler-Nichols continuous-cycling tuning from ultimate gain ku
  and ultimate period tu: kp = 0.6 * ku, ki = 2 * kp / tu,
  kd = kp * tu / 8.
- Structural sanity for PID gains: kp > 0, ki >= 0, kd >= 0.
- Python control tooling (control, slycot) computes margins, root
  locus, and Bode plots for iteration.

## Workflow

1. Build the plant model as a transfer function or state-space
   system.
2. Compute gain and phase margins from the open-loop response and
   check them against the acceptance minima with
   scripts/python_control_logic.py.
3. Classify closed-loop stability from the margins.
4. Tune an initial PID with Ziegler-Nichols and sanity-check the
   gains.
5. Iterate with root-locus/Bode analysis until the margins pass.

## Pitfalls

- Calling the loop stable from a single positive margin.
- Tuning PID gains without checking the ultimate gain/period
  validity.
- Mixing dB and ratio margin values in one comparison.
- Accepting negative integral or derivative gains silently.

## Behavior contract (gate 3)

The margin, stability, and tuning logic is exercised by the gate 3
contract test: scripts/test_python_control.py against
scripts/python_control_logic.py (stdlib unittest, offline). Run:
python3 scripts/test_python_control.py

## Compliance

- ARP4754A is proprietary (SAE); name + paraphrase only per
  standards-map.yaml and brief 06 (revision note: ARP4754B
  supersedes; this skill keys to A, the certification-baseline
  revision).
- compliance: STANDARDS-REF, gated: false.