In this paper, the problems of output feedback robust approximate pole assi
gnment (OFRAPA) and robust output feedback stabilization (ROFS) are conside
red. The idea is to search for an optimal output feedback gain matrix such
that objective functions defined via appropriate robustness measures and po
le assignment constraints can be optimized using a genetic algorithm (GA).
The nature of the GA renders it suitable for optimizing non-smooth objectiv
es such as that involving computation of the spectral condition number or t
he real stability radius. Furthermore, constraints on the elements of the f
eedback gain matrix can be catered for naturally in the GA parameter encodi
ng procedure.