Skip to main content

Challenges of modeling a physical system

Short answer

Challenges include complexity, nonlinearities (friction, saturation), uncertain parameters, unmodeled dynamics, measurement difficulty, and disturbances. Overcome by linearizing around operating point, system identification, robust control with safety margins, feedback, filtering, and adaptive control or gain scheduling.

What are the challenges of modeling a real physical system and how can you overcome it?

A model is a mathematical description (equation or transfer function) of how the plant output responds to its input. Real systems are hard to model.

Challenges

  • Complexity: many interacting parts, so a full model is large; some physics is not understood.
  • Non-linearity: friction, saturation, dead zone, backlash; linear models hold only near an operating point.
  • Uncertain and changing parameters: mass, friction and temperature change with time and load.
  • Unmodelled dynamics and delays: sensor lag, actuator delay and noise.
  • Measurement difficulty: parameters cannot always be measured directly; sensors are noisy.
  • Disturbances that are random or unknown.

How to overcome

  • Use simplified models valid around the operating point (linearisation) and keep only the dominant dynamics.
  • Identify the model experimentally (step-response or system identification) and verify with measurements.
  • Include safety margins in the design (robust control) and use feedback, which tolerates model error.
  • Use adaptive control or gain scheduling when parameters change.
  • Filter sensor noise, and test the model and controller by simulation then on the real hardware.

✓ Answer checked by Claude Opus 5.5 (high effort)

Related questions

All Embedded System chapter 7 questions →