Research On The Algorithm For Steady-state Optimizing Control Of Industrial Processes

Offline optimization method is a kind of idealized method. Although the normaloperation of industrial process according to certain design, the change of environment,catalyst aging and the change of raw material composition form the disturbance ofindustrial process. So the condition of the original design can not achieve the optimaloperating conditions. The system optimization and parameter estimation (ISOPE) is aneffective method for solving the object model mismatch practical industrial processproblems.In this paper, on the basis of the existing ISOPE methods, we propose a newalgorithm which can solve the problem of industrial process steady-state optimizationcontrol. The main content of the thesis research and the results are as follows1, This paper proposes a new algorithm to find the optimal solution for industrialprocess steady-state optimization control problems. Compared with the existing ISOPEmethods, the least squares method is used to estimate the process derivatives. Theestimation method can avoid the noise interference, choose the set points easily, and wecan get the result soon.2, In order to illustrate the effectiveness of the algorithm, which is applied toseveral real industrial processes, the simulation results show the validity of thealgorithm.