Feedback loop
Closed-loop control, gain, delay, oscillation, nested control loops, and the simple but expensive question of what happens when a sensor remains plausible while lying.
ROBOTICS + CYBERNETICS / ACTIVE DEPARTMENT
MAKE THE LOOP SURVIVE REALITY.
Sensing, actuation, feedback, myoelectric control, assistive systems, embedded hardware, haptics, failure behavior, and the messy boundary where machines stop being diagrams and start touching people.
5 LIVE TECHNICAL PIECES2 REFERENCE ROUTESOPEN FAILURE QUEUE
CURRENTLY PUBLISHED
Control begins with a measurement that can be wrong.
Cybernetics is treated here as a systems problem: intent, sensing, error, delay, feedback, adaptation, failure, and the operator's ability to recover when the controller's model stops matching the physical world.
Myoelectric control
Surface EMG, biological variability, user adaptation, noisy intent, haptic feedback, and why a controller that guesses wrong can feel worse than a simpler system that obeys cleanly.
Graceful degradation
Assistive and robotic systems should not move directly from full capability to chaos because one local component failed.
CONTROL + PERCEPTION / FIELD GUIDES
The failure modes live between the blocks.
Three new guides push beyond the block diagram into timing, uncertainty, actuator limits, and the evidence required to know when the loop has stopped behaving like the model.
FIELD GUIDE 001 / CONTROL
Control Loops Hate Delay
Latency becomes phase lag. Sampling, filters, estimator age, actuator response, network jitter, and implementation timing can spend stability margin until correction arrives too late.
Read control guide → FIELD GUIDE 002 / PERCEPTIONSensor Fusion Does Not Create Truth
Fusion is state estimation under uncertainty. Correlated errors, timing, coordinate frames, bias, observability, outliers, and miscalibrated covariance can make several sensors confidently wrong together.
Read perception guide → FIELD GUIDE 003 / ACTUATIONActuator Saturation Is a Control Problem
Integrator windup, rate limits, control authority, thermal derating, redundant effectors, command shaping, and what happens when requested effort exceeds what hardware can physically deliver.
Read actuation guide →WORKING QUESTIONS
The hand is easy. The hand after six months is the problem.
Real-world robotics is dominated by repeated loading, contamination, sensor drift, wiring fatigue, calibration change, thermal limits, serviceability, user adaptation, and failure cases that rarely appear in polished demonstrations.
Low-cost robotic hand failure modes
Identify which joints, transmissions, fasteners, sensors, tendons, bearings, wiring paths, and control assumptions dominate failure under repeated use.
How much tactile feedback is enough?
Separate novelty from measurable improvement in grasp control, object protection, force estimation, fatigue, and user confidence.
Adaptive intent prediction
Test where prediction improves myoelectric control and where it turns assistive technology into automation that argues with its user.
Bench safety before human contact
Develop practical tests for pinch, runaway motion, force limits, thermal hazards, electrical faults, sensor loss, watchdog recovery, and safe-state behavior.
DEPARTMENT RULE
Bodies are not beta hardware.
Assistive and human-contact systems need explicit failure limits, override paths, maintenance assumptions, and evidence that the user can recover control. Clever prediction is subordinate to safe behavior.