Although l(1)-optimal linear state feedback controllers are known to be dynamic, it has been shown that suboptimal performance arbitrarily closed to optimal can be achieved by using a static non-linear feedback law. In this paper, this fact is established by using a novel approach which shows that the result is a natural consequence of elementary state-space theory. The approach is motivated by recent works in active vision systems, which have considered a state-feedback problem tightly connected with l(1) optimization. This problem, which has independent interest, is discussed in some detail. The new formulation of the problem provides additional insight in l(1) state-feedback. In particular, it leads naturally to some extensions which do not follow in a straightforward manner from previous works on the subject.