A practical robot control design problem typically consists of several performance requirements. The control designer may need to take into account a few of different design specifications together. Therefore, there exists a need for a methodology to address the design of a controller to satisfy multiple specifications. The objective of this thesis is to develop a controller design method to meet multiple simultaneous specifications (MSS), and apply it to robot trajectory tracking systems. Also called 'convex combination' design method is proposed to solve the MSS control problem. Through a linear system framework, the design specifications are described and considered uniformly. When the specifications have this convex property, the proposed method offers a two-stage strategy that can effectively design the controller to meet multiple specifications at the same time. The design strategy is straightforward and easily implemented. Further, through feedback linearization, this proposed linear design method is applied to nonlinear robot tracking systems to solve the MSS problem. Under imperfect linearization conditions due to system uncertainties, system robustness is viewed as one of multiple specifications to be met, and the convex combination method can also be validated. The application is conducted through simulation and experimentation on one commercial robot, and the proposed design method is verified to be effective in practice. By arriving at the thesis objective, industry will have at its disposal, a performance oriented automated control design procedure. The further impact of this thesis is that new tasks that have never been done before may be automated.