Control Loop Diagnostics for Robotics
Debug PID systems and control loops with data-driven diagnostics
What You Can Do
You can upload time-series control loop data and Claude will diagnose oscillations, identify stability issues, and evaluate tuning parameters. The skill analyzes your signal characteristics, quantifies steady-state error and overshoot, and generates actionable tuning recommendations backed by system identification metrics. You'll receive prioritized root-cause analyses and concrete parameter adjustment guidance to stabilize your feedback control systems.
Features
distinguish between sensor noise, PID tuning problems, and fundamental instability
assess proportional, integral, and derivative gains against ideal ranges for your system type
decompose noise from real system dynamics using frequency-domain inspection and step-response metrics
quantify offset, settling time, overshoot, and rise time against performance targets
compute phase margin, gain margin, and damping ratio from your measured response data
generate specific Kp/Ki/Kd adjustment suggestions with predicted impact on system behavior
evaluate before/after control loop performance across multiple tuning iterations
structured findings with visualizations, severity ratings, and implementation priority
Example Output
Example 1: Oscillation Diagnosis
- 🔴 CRITICAL: Sustained oscillation detected
Frequency: 12 Hz | Amplitude: ±2.3V | Damping ratio: 0.15 (unstable)
Root Cause: Over-tuned derivative gain amplifying sensor noise
Recommendation: Reduce Kd from 0.85 to 0.35, add 50ms low-pass filter
Example 2: Tuning Adjustment Report
- ✅ Current: Kp=1.2, Ki=0.05, Kd=0.8
- ⚠️ Issues: 18% overshoot, 320ms settling time (target: 200ms)
- ✅ Proposed: Kp=0.8, Ki=0.08, Kd=0.4
- 📊 Expected improvement: 6% overshoot, 185ms settling, ±0.02V steady-state error
What's Included
- SKILL.md: Complete diagnostic workflows for PID analysis, sensor evaluation, and root-cause debugging
- PID Tuning Template: Step-by-step worksheet for documenting system characteristics and evaluating parameter ranges
- Data Analysis Checklist: Verification steps for signal quality, noise floor assessment, and stability metrics
- Signal Inspection Guide: Decision tree for identifying oscillation sources (derivative kick, integral windup, sensor noise)
- System Identification Reference: Quick-lookup tables for expected response characteristics by control system type
- Diagnostic Report Template: Structured format for findings, severity levels, and prioritized recommendations
Who It's For
- Robotics engineers tuning motion control and joint feedback loops
- Control systems engineers troubleshooting PID implementations
- Hardware engineers debugging actuator response and stability issues
- Embedded systems developers integrating servo motors or stepper feedback
- Mechanical engineers optimizing precision positioning systems
Best For
- Diagnosing oscillating or unstable control loops
- Evaluating and adjusting PID tuning parameters
- Distinguishing sensor noise from real system problems
- Analyzing step response data and identifying transient issues
- Creating diagnostic reports and tuning change justifications
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