Studies On Real-Time Optimization Of The Tennessee Eastman Challenge Problem

With the resource shortages, higher energy prices and the increasingly competing markets, it has become more and more intensive for companies to seek to the maximum production efficiency. At the same time, in the presence of process complexity, the traditional off-line optimization techniques are unable to meet the economic requirements of productions. In this context, real-time optimization technology has become an emerging research area in the process control community.This paper investigates real-time optimization of industrial systems from the perspective of the practical application, in which the TE process is considered. Firstly, an in-depth analysis of TE process is carried out. Based on the previous researches of TE model, the requirements of real-time optimization of the overall process, material balance and energy balance model are proposed, along with the complete mechanism of TE process model as well as the corresponding adjustment factors.After that, the paper deeply investigates the steady-state optimization problem for TE process, in which the nonlinear programming method is utilized to solve the optimization. This method enjoys quick and efficient solutions of non-linear optimization of such complex computational problems. The TE simulation platform is used as a test-bed for carrying out the studies on the impacts of model uncertainty on the results of steady-state optimization.Finally, the paper presents a real-time optimization scheme for TE process, including steady-state analysis, data correction, model updating and optimization calculating. By means of experimental simulation, the impact of the offset in terms of steady-state operating point on the optimization process is discussed, thereby laying the foundation for the implementation of real-time optimization strategy.