کنترل کننده عملکردی پیشگویانه متناسب با انتگرال ساختار رگلاتور بهینه مشابه : مقایسه با کنترل کننده های سنتی پیشگویانه عملکردی و کاربرد های تجهیزات سنگین نفت زغال سنگ

By extending the system's state variables, a novel predictive functional controller has been developed. The structure of this controller is similar to that of classical proportional integral (PI) optimal controller and includes a control block that can perform a feed-forward control of future P-step set points. It considers both the state variables and the output errors in its cost function, which results in enhanced control performance compared with traditional state space predictive functional control (TSSPFC) methods that consider only the predictive output errors. The predictive functional controller (PFC) has been compared with TSSPFC in terms of tracking ability, disturbance rejection, and also based on its application to heavy oil coking equipment. The results obtained show the effectiveness of the controller.

The optimal control of the synthesis of petrochemicals and other related processes is of considerable significance because good control results markedly improve the dynamic performance and also enhance economic benefits. Therefore, predictive functional control (PFC)[ 1-31 has gained tremendous success in industrial applications. It is categorized under model predictive control (MPC)[4,5] and was first presented by Richalet and Kuntze. The control law is based on the prediction obtained from the model of the processes. Control action is calculated by minimizing the difference between the predicted process output and the reference signal over a certain time horizon. It has been proved that PFC exhibits remarkable robustness despite the model mismatch and uncontrolled dynamics[6- 111. While retaining the good features of MPC, PFC makes the control input more regular, which considerably reduces the control- calculating burden, and therefore it is highly applicable to those processes that need fast control. Till now, several research studies have been performed on PFC theory, and studies with regard to its application have made the PFC theory more significant. However, by selecting the state space model, the system’s inner states can be easily described and information of these states such as state feedback and state constraints can be effectively used when the controllers are designed[ 11-13]. If the states represent some physical variables, prediction of their future changes can also give important information regarding the processes. But the state space PFC algorithms that have been presented till now have not made full use of these merits[l,l I]. Based on the above-mentioned merits of statespace design, a novel predictive functional control method has been developed. The structure of this controller is similar to that of proportional integral (PI) optimal regulator [ 141 and has P -step setpoint feedforward control. Simulation comparisons and application study show that this method has tremendous applications in chemical engineering.

A novel predictive functional control method (QPISPFC) has been presented in this article paper. As seen from the comparisons with TSSPFC, QPISPFC controller exhibits an improved regulatory capacity for both reference input tracking and load disturbance rejection. Application to the coking of residues oils process equipment also displays good control performance.