A state estimator design for multimodal adjustment process using genetic algorithm

This article proposes a new kind of static state estimator based on Genetic Algorithms (GAs) in order to accomplish an estimation-based search techniq ue for multimodal adjustment processes. To adapt GA to the estimation probl em, the general procedure of the conventional GAs are modified in two aspec ts; first, the reproduction strategy uses two different criteria (survival cost and parent cost) for the elimination of weaker members and parent sele ction, and secondly, a new genetic operator based on a priori knowledge of the system is developed to generate more effective offspring solutions. The performance and applicability of the proposed estimator was investigated v ia three numerical examples of the multimodal adjustment system, and the re sults obtained show that this estimator performs very well even with the pr esence of a large amount of measurement noise. (C) 1998 Elsevier Science Lt d. All rights reserved.