Robust pole placement using genetic algorithms

This paper presents the application of genetic algorithms (GAs) to the robust pole placement for LTI systems with parameter uncertainties. The robust pole placement approach is firstly converted to a constrained optimization problem. The objective of the optimization is to derive the most robust state-feedback gain matrix K with respect to parametric plant uncertainties. Then, GAs are introduced as efficient optimization tools to solve the problem. The search of the GA is done within the linear bounded domain in the space of parameters in matrix K. The resulting system guarantees the closed-loop poles to remain in a prescribed region in the complex plane despite of the greatest possible uncertainty in plant parameters. Finally, this method is applied to design the longitudinal stability augmentation system (SAS) for a static unsteady airship. Simulation results show that the designed system not only stabilizes the longitudinal motion of the airship, but also reduces the sensitivity to parameter uncertainties.