Performance optimization of gas turbine engines using the studga

Abstract

Abstract Control of gas turbine engines is concerned with producing adequate thrust while maintaining stable and safe operation. Additional control layers can allow improvements in engine performance. Performance optimization can be expressed in terms of: minimizing fuel consumption while maintaining nominal thrust output, maximizing thrust for the same fuel consumption and minimizing turbine blade temperature. A new evolutionary approach called the StudGA is used as the optimization framework to design for optimal performance in terms of the three categories above. This approach gives faster convergence and can potentially save on expensive simulations. Model-based experimental results are used to illustrate these approache