Efficient Optimization of Large k Real-time Control Algorithm

Authors:

Delphi Delco Electronics Systems
Restraint Systems Electronics
Kokomo, IN 46904-9005
E-mail: pjschube@mail.delcoelect.com
Phone: 765-451-3615
Fax: 765-451-3600

Daniel H. Loughlin
Civil Engineering Department
North Carolina State University
CB7908
Raleigh, North Carolina 27695-7908
E-mail: dhloughl@eos.ncsu.edu
Phone: 919-515-7738
Fax: 919-515-7908

Abstract:

Resource requirements for global optimization increase dramatically with the number of real-valued decision variables (k). Efficient search strategies are needed to satisfy constraints of time, effort, and funding. In this paper, a conjunction of several disparate methods is used to automatically calibrate a non-linear real-time control used in the automotive industry. By combining a response surface methodology with a hybrid genetic algorithm search, air-bag deployment calibrations can be automated, producing solutions superior to conventional manual search.

Keywords:

design of experiments, genetic algorithms, simplex, Powell, optimization, automated, hybrid, large k, automotive, embedded control