The identification of models from experimental data is the first step in model-based control design. Furthermore, when the model is of high order, it is normal to reduce the model order for a simpler controller design. Low order identified models are the fundamental elements for the design of practical control systems.

Chapter Contents:

• 5.1 Introduction
• 5.2 General procedure
• 5.3 Example 1: Second order inverse response model identification
• 5.3.1 Problem statement
• 5.3.2 Dimensionless representation of second order inverse response model
• 5.3.3 Identification procedure
• 5.3.4 Application examples
• 5.4 Example 2: Reduced effective transfer function reduction for PID decentralized control
• 5.4.1 Problem statement
• 5.4.2 Dimensionless representation of the reduced effective transfer function
• 5.4.3 Inverse response analysis
• 5.4.4 Reduced order model: general case
• 5.4.5 Reduced order model: particular cases
• 5.4.6 Application examples
• References

Inspec keywords: reduced order systems; control system synthesis; identification

Other keywords: model order reduction; dimensionless system identification; low order identified models; model-based control design

Subjects: Simulation, modelling and identification; Control system analysis and synthesis methods