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