An Optimal Control Method for Operation Status Migration in the Process Manufacturing Industry

The process manufacturing industry plays a pivotal role in the manufacturing industry. It is characterized by frequent fluctuations in inlet conditions, frequent changes in operating conditions, and numerous random disturbances. It is challenging to achieve the optimal operation of the whole process by ignoring the changes in operation status and only requiring the key technical indicator to be close to the optimal setpoint. To this end, this paper proposes an optimal control method for operation status migration in the process manufacturing industry. First, a method for defining and classifying operation statuses based on mechanism knowledge is proposed. Then, construct a nonlinear process description model and propose an online spatiotemporal recognition method for operation status. Finally, with the objectives of minimal consumption, system stability, and approach to the optimal setpoint, an optimal control model for optimal migration of operation statuses is constructed to obtain the optimal control quantities and achieve optimal operation. The experimental results show that the proposed method can reduce resource consumption by finding the optimal migration path of the operation status to ensure system stability and product quality, which is of great significance for actual production.