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Automatic control : control system identification (AU-ID)

Identify a process to build a mathematical model from inputs/outputs recording

Specifying tests

Choose test scenarios – Choose sample time – Anti-aliasing filters – Conduct tests – Closed loop tests

Understanding numerical identification

Define identification goals – Analyze test results – Set numerical identification process – Closed-loop identification – Validate an identified model

Discovering identification methods

Simple least squares methods – Recursive least squares method – Unbiased estimators method – Instrumental variable methods – Generalised least squares method – Extended least squares method – Output error method

Identify nonlinear systems

Principle – IT structure to build – Application with an example

Educational objectivs

  • implement several identification methods
  • identify linear systems with varying parameters
  • identify nonlinear systems

Expected benefits

  • obtain identified systems as fast as possible

Information

Duration: 1 day

Target audience:

  • engineers
  • senio technicians

Training level:

  • apprenticeship
  • technical subject

Prerequisites:

  • deepen knowledge of dynamic systems representation

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