Gas turbine engine controller design using multiobjective genetic algorithms

This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. It is shown how the MOGA confers an immediate advantage over conventional multiobjective optimization methods by evolving a family of Pareto-optimal solutions allowing the control engineer to examine the trade-offs between the different design objectives. In addition, the paper demonstrates how the genetic algorithm can be used to search in both controller structure and parameter space thereby offering a potentially more general approach to optimization in controller design than traditional numerical methods.