Linear matrix inequalities for rank one robust synthesis

This paper treats synthesis of robust controllers for linear time-invariant systems. Uncertain real parameters are assumed to appear linearly in the closed loop characteristic polynomial. Robustness of such systems can be maximized by convex optimization over an infinite-dimensional space. Here it is shown that finite-dimensional restrictions of this problem can be stated as minimization under linear matrix inequality constraints. This allows application of more efficient algorithms.<>