Genetic model reference adaptive control

摘要

A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. Motivated by the past GA's use in off-line design of controllers we introduce a new approach to adaptive control, which we call "genetic model reference adaptive control" (GMRAC), where a GA manipulates a set (population) of parameterized controllers and selects the controller most capable of providing good performance for current plant operating conditions. The performance of GMRAC is evaluated for a cargo ship steering application.