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Recently there has been an increasing interest in the application of computer algebra to control system analysis and design. Control system design is to find out feasible parameters to be designed for which a target system satisfies given control design specifications. Many important control system design problems are regarded as parametric and non-convex optimization problems. We have been developing a Maple toolbox for robust control via a parameter space approach based on symbolic computation. First we explain how we can practically solve such control system design problems by using algebraic methods, quantifier elimination. Then we show an effective visualization of the results i.e. the feasible regions of design parameters in a parameter space. All these results are implemented as the Maple toolbox for parametric robust control.