To solve the problem of optimal real-time control and large memory expense of partial differential equation（PDE）model with constraints，an approach is presented for optimal control with input/state constraints based on reduced-order model，which was derived from dynamic PDE in the form of a discrete-time low-order state-space model with high accuracy by using proper orthogonal decomposition（POD），singular value decomposition（SVD）and Galerkin projection. Then，by combining the reduced-order model

the modified optimal control method

the single-step rolling optimal control with certain input/state constraints based on quadratic programming which was demonstrated with the extremum validating optimal control based on linear quadratic regulator each other

was constructed. The controlling simulation results in the convection-diffusion-reaction process showed the efficacy and accuracy of proposed algorithm.