Robust control system design using simulated annealing

Toshikazu Motoda, Robert F. Stengel, Yoshikazu Miyazawa

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Design parameters of a flight control system are optimized by a probabilistic method. Simulated annealing is applied for the optimization, and the downhill-simplex method is added to generate new design vector candidates. The cost function to be minimized is chosen as the probability of violating the design criteria, and it is derived by Monte Carlo evaluation that incorporates various uncertainties. Thus, the designed system is robust against these uncertainties. The feasibility of the algorithm is demonstrated by designing a control system for a simplified model. The results show that simulated annealing is more effective than the downhill-simplex method for parameter optimization, and it requires less computational time than the genetic algorithm. The Automatic Landing Flight Experiment unpiloted reentry vehicle provides a second example. Simulated annealing is shown to produce a more robust longitudinal flight control design than that used in the 1996 flight experiment.

Original languageAmerican English
Pages (from-to)267-274
Number of pages8
JournalJournal of Guidance, Control, and Dynamics
Issue number2
StatePublished - 2002

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Aerospace Engineering
  • Space and Planetary Science
  • Electrical and Electronic Engineering
  • Applied Mathematics


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