Although it is still common in the field of motion control systems to first design the structure and then the controller, integrated design approaches are becoming more popular. The problem of finding optimal parameters for a parameterized structure and controller by solving an optimization problem will be referred to as \textit{controller-structure optimization} (CSO). These types of problems are often characterized as multi-objective and non-convex and therefore hard to solve. Especially if the parameterized structure is modelled in a finite-element (FE) environment. This MSc thesis report presents a design approach for solving a CSO problem by using an approximate model of the parameterized structure in the form of a \textit{parameter-dependent state-space} (PDSS) model. The PDSS model is obtained by taking a few samples of the original structure. Each of these samples represents a \textit{linear time-invariant} (LTI) modal reduced state-space model. The main emphasis of this MSc thesis is to investigate whether this approach is able to approximate the solution of the original (comprehensive) CSO problem in an efficient way.