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IBR Identification and Learned-Model Validation

Excitation, Observation, and Identifiability

T1-01 · Module outline

Define what the measurements can reveal about selected parameters.

Learning objectives

  • Declare observed and latent variables.
  • Relate excitation to parameter sensitivity.

Concept outline

  1. Terminal measurements and hidden controller states
  2. Excitation and sensitivity
  3. Selected parameters and information limits

Experiment direction · Planned

Simulation and code experiment

Compare parameter sensitivity under two excitation patterns.

Model explanations, parameter settings, runnable code, and result interpretation will be developed here.

Practice and discussion

State which parameters the experiment intends to estimate.

Worked solutions and feedback will accompany the full lesson.

Material preparation

Related research cases or review records are available and need adaptation into a lesson with a declared scope.

Adapt the existing material into a lesson, a reproducible experiment, and worked practice.

All modules in this course
  1. Excitation, Observation, and Identifiability
  2. Parameter–Residual Compensation
  3. Configuration Uncertainty and Fair Baselines
  4. Independent Validation of Learned Dynamics