Smallest ball containing given balls. Let Bi, i = 1, 2, . . . m, be m given Euclidean balls in Rn, with centers xi, and radii i > 0. We wish to find a ball B of minimum radius that contains all the Bi, i = 1, 2, . . . m. This is used in robust control to have a simpler representation of uncertainty where one ball covers all possible values of the uncertain parameter. Cast this problem into a known convex optimization format. In other words, formulate this as a convex optimization problem with m constraints, something that one can implement using available toolboxes