Modern large-scale industrial control systems adopt hierarchical structures, where the advanced process control with model predictive control (MPC), as its representative, has been considered one of the most important achievements. The two-layered structure, i.e., the steady state optimization layer and the dynamic control layer, is dominant in the industrial MPC technology. The two-layered MPC can effectively handle the multi-objective optimization and multi-variable control problems in the complex processes. The algorithm of two-layered MPC is briefly summarized. The compatibility and uniqueness of the steady state solutions for the multi-variable MPC are analyzed based on the steady-state relationship between the control inputs and the controlled outputs, demonstrating the importance of the steady state optimization. Viewpoints are presented on issues such as performance comparisons between two-layered MPC and zone MPC, the singularity of the steady-state model, and the dynamics of the closed-loop system. Topics requiring further researches are pointed out.