Regulator Design using a Multiobjective Genetic Algorithm

When designing a regulator for a specific system, a set of different objectives needs to be evaluated. This is usually done by manual tuning of parameters and evaluation of the step response. In recent years gradient-based multiobjective constraint optimization methods have been successfully applied on this problem while, in this report, a multiobjective genetic algorithm approach is applied. By defining a set of cost-functions in the frequency-domain for different frequency intervals, PID regulator settings for two bench-mark models are identified and successfully evaluated.