Min-max predictive control of a linear state-space system with a bounded set of input matrices is studied based on a quadratic performance criterion. Systems with stable and integrating dynamics as well as time-varying and time-invariant uncertainties are treated. Algorithms that are computationally manageable and ensure closed-loop stability are developed and tested.