This paper presents a multi-step predictive control algorithm for input saturated systems by designing a sequential optimization scheme. The control inputs are divided into several subsets, and only one subset of inputs are optimized at each time instant. The inputs that are not optimized at the current instant remains the latest optimized one. For each input set, a set invariance condition is identified, and the multi-step predictive controller design problem is transformed into a “min-max” optimization problem. The multi-step predictive controller is obtained by solving linear matrix inequalities(LMIs). The simulation results show that the proposed multi-step predictive control algorithm has the advantage in reducing the computation time in controller design.