Accurate control of gas odorization concentration plays an important role in ensuring the safe transportation and use of gas. However, due to the lack of monitoring of the actual odorization effect at the end-users, the existing linear control algorithm represented by the gas flow rate proportional open-loop control is difficult to achieve a good control effect. For this reason, based on the least-squares identification of the open-loop step response and taking the odorant concentration at the gas end-users as the control object, a CARIMA model of the gas odorization process is established, and an improved generalized predictive control algorithm is proposed on the basis of the traditional generalized predictive control, and the feasibility of this control algorithm is verified by the simulation tests and field experiments of the gas odorization control. The research results show that compared with the conventional gas flow rate proportional openloop control, the improved generalized predictive control algorithm can accurately control the odorant concentration at the end-users in real-time online, with the steady-state error of less than 2 mg / m 3 , the overshoot of less than 10% when the working condition changes, and the average absolute error of less than 1. 5 mg / m 3 , which can meet the need of accurate control of gas odorization process. The research results improve the efficiency and quality of gas odorization while playing a role in saving costs and improving gas safety, which has good application value.