l1-suboptimal pole placement design

We incorporate an arbitrary number of "candidate" positive distinct poles into the scalar l₁ optimization framework in order to obtain low-order rational suboptimal solutions to constrained l₁ optimization problems. Our approach uses a single linear program to minimize an upper bound on the l₁ norm and gives a solution which uses only the best out of the prespecified poles. Rational suboptimal solutions to a scalar two-block problem are obtained similarly.