This analysis formulates an approach for converting minimax LQ (linear-quadratic) tracking problems into LQ regulator designs, and develops a Matlab application program to calculate an H-infinity robust control for discrete-time systems with perfect state measurements. It uses simulations to explore examples in financial asset decisions and utility input purchasing, in order to demonstrate the method. The user is allowed to choose the parameters, and the program computes the generalized Riccati Equation conditions for the existence of a saddle-point solution. Given that it exists, the program computes a minimax solution to the linear quadratic (LQ) soft-constrained game with constant coefficients for a general scalar model, and also to a class of matrix systems. The user can set the bound to achieve disturbance attenuation.