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Constrained H2 approximation of multiple input-output delay systems using genetic algorithm.

Haiping Du1, James Lam, Biao Huang

  • 1Mechatronics and Intelligent Systems, Faculty of Engineering, University of Technology, Sydney, P.O. Box 123, Broadway, NSW 2007, Australia. hdu@eng.uts.edu.au

ISA Transactions
|March 14, 2007
PubMed
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A novel genetic algorithm method approximates multiple input-output delay systems, minimizing H2 error while constraining H(infinity) error and steady-state response. This approach yields superior approximation performance compared to prior methods.

Area of Science:

  • Control Systems Engineering
  • Computational Intelligence
  • Systems Approximation Theory

Background:

  • Accurate modeling of multiple input-output delay systems is crucial for control design.
  • Existing approximation methods may not adequately balance different performance metrics.

Purpose of the Study:

  • To develop a constrained H2 approximation method for multiple input-output delay systems.
  • To utilize a genetic algorithm for optimizing model approximation under specific constraints.

Main Methods:

  • A genetic algorithm was employed to minimize the H2 error between original and approximate models.
  • Constraints were imposed on the H(infinity) error and steady-state response matching under step inputs.
  • A parameter search space expansion scheme was integrated into the genetic operations.

Related Experiment Videos

Main Results:

  • The proposed genetic algorithm method effectively minimized H2 error.
  • Approximate models achieved better performance in H2 and H(infinity) norms.
  • Improved steady-state response matching was observed compared to gradient-based methods.

Conclusions:

  • The constrained H2 approximation using a genetic algorithm is effective for multiple input-output delay systems.
  • This method offers improved approximation accuracy and performance metrics.
  • The approach provides a viable alternative to existing model approximation techniques.