Genetic adaptive state estimation for a jet engine compressor

A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. In this paper we develop a GA that can perform online adaptive state estimation. First, we show how to construct a genetic adaptive state estimator where a GA evolves the model in a state estimator in real time so that the state estimation error is driven to zero. Next, we show how to use a genetic adaptive state estimator for predicting when surge and stall occur in a nonlinear jet engine compressor model.