In this paper a fixed state feedback control law which minimizes upper bounds on linear-quadratic performance measures for m distinct plants is studied. Previous work  by the authors demonstrated a convex semidefinite programming solution thereby guaranteeing global optimality. The present work extends that result by proposing an algorithm which reduces the conservatism of the minimum guaranteed-cost upper bounds for each of the m performance measures.
NASA University Research Centers
simultaneous stabilization, simultaneous control, semidefinite programming, state feedback control, linear matrix inequalities
Abdallah, Chaouki T.; Robert A. Luke; and Peter Dorato. "A Reduction in Conservatism for Convex Linear-Quadratic Simultaneous Performance Design." (2012). http://digitalrepository.unm.edu/ece_fsp/113