We present a novel MPC algorithm without terminal constraints and/or costs, for which the prediction horizon is reduced in comparison to standard MPC while asymptotic stability and inherent robustness properties are maintained. To this end, we derive simplified stability conditions and investigate the interplay of open and closed loop control in MPC. The insight gained from this analysis allows to close the control loop more often while keeping the computational complexity of basic MPC. Our findings are verified by numerical simulations. (C) 2017 Elsevier Ltd. All rights reserved.