A general methodology is presented for the multiobjective optimization of actively controlled structures. The methodology can handle structures involving precise as well as fuzzy data. The concepts of fuzzy set theory and game theory are combined to present a new solution procedure for solving a general structural optimization problem involving multiple objectives. The design of a crisp (traditional or well-defined) multiple objective problem can be considered as a special case of the present approach. The methodology used in this work ensures that the control law is optimal even in the presence of uncertainties and variations in the system parameters. The efficiency of the methodology is illustrated by considering the design of an actively controlled truss structure with structural weight, controlled system energy, stability robustness and performance robustness as objective functions and the cross sectional areas of members as design variables. The quantitative aspects of the optimum solution are demonstrated through transient response simulations. The numerical results demonstrate the effectiveness of the procedure in finding the best compromise solution to the multiple objective structural design problem.