Up to now the parameter space approach was either utilized for robustness analysis or for design of fixed gain controllers. This paper presents an extension of this method which allows the design of gain scheduling controllers which simultaneously stabilize a finite number of representatives of an uncertain plant. The approach is applied to an automotive control example. 1 Introduction The parameter space approach can be used for design of controllers and robustness analysis of linear uncertain plants. In general, the approach requires a physically motivated modelling of the plant, i.e. the uncertain parameters have a physical relation, for example masses, lengths, etc. For convenience the uncertain parameters are gathered in q = [q 1 : : : q ` ] T , an uncertainty vector, where ` denotes the number of uncertain parameters. Each of the q i lies in an interval q i 2 [q \Gamma i ; q + i ]. In the case of independent uncertain parameters the uncertainty domain Q = fq i j q i 2 [q ..