Improved Predictive Functional Control Based on Unmodeled Dynamics Compensation for Ethylene Cracking Furnace

The process of controlling the outlet temperature in ethylene cracking furnaces exhibits notable nonlinearity. Variations in feedstock and fuel properties prevent accurate modeling, resulting in suboptimal performance of predictive functional control in practical implementations. This research analyzes the causal linkage between outlet temperature and fuel gas flow rate. A mechanism model is derived along with its input–output characteristics, and the controlled object is represented as a composite state-space system combining a linear model with unmodeled dynamics. By using the available unmodeled dynamics values from the previous time and the tracking errors caused by their increment, a state-space compensation performance index for unmodeled dynamics is designed. This index is based on the closed-loop system established by a predictive functional controller developed for the linear model. An innovative compensation strategy is developed to mitigate unmodeled dynamics’ impact on the closed-loop system, resulting in an improved predictive functional control approach for ethylene cracking furnace temperature regulation. The closed-loop system’s input–output relationship is formulated, and system stability and convergence are rigorously analyzed. Experimental validation at a petrochemical plant in Northeast China demonstrates that the proposed method reduces the mean squared error by 48.72% and the integrated absolute error by 30.52% when compared to the current method.