To reduce the computational complexity of the dynamic optimization section in model predictive control algorithm，a new method based on linear programming instead of quadratic programming was proposed.For both single-input single-output and multi-input multi-output model predictive control，the linear programming problem to describe the dynamic optimization is constructed by treating control increment，output increments and some deviation variables as optimization variables，inducing equality or inequality linear constraints and choosing a linear objective function.Moreover，soft constraints can be considered as a part of the linear programming problem to improve the performance indicators of dynamic process and to achieve the purpose of smooth control.Finally，a simulation example illustrates the effectiveness of the presented approach.