BackgroundProcess modeling of chemical systems has important directive significance to the analysis and optimization of actual production processes and the improvement of economic efficiency. However, existing iterative methods struggle with initial value selection and lack of generality when applied in modeling with the sequential module method, making it challenging to solve both unconstrained and constrained iterative problems in the modeling. Therefore, it is necessary to design a new iterative method. MethodsA dynamic iterative method for sequential module steady-state modeling is proposed. The sequential module method is used to establish a steady-state sequential model of a chemical system, and a dynamic feedback link is added outside the model. This feedback link can make its iterative output converge to the next step system output by learning the deviation between two or more steps in the iterative process, thus ensuring the convergence of the process modeling and improving the iteration speed of the modeling. In order to improve the generality of the dynamic iterative method and reduce the difficulty of selecting the initial value of iteration, both proportional and integral actions are added to this method according to the principle of automatic control. Significant FindingsThe modeling results show that adding dynamic feedback links outside the model effectively resolved the algebraic loop problem and improved the speed of system convergence. The inclusion of both proportional and integral actions in the dynamic iterative method effectively reduced the sensitivity to initial value and improved the generality of the method. This method is applied to the fluid catalytic cracking unit reaction-regeneration system and its effectiveness is demonstrated by solving both unconstrained and constrained iterative problems.