Modeling and nonlinear predictive functional control of liquid level in a coke fractionation tower

The level control of the fractionation tower in industrial coke unit is not very easy due to its complex characteristics and nonlinearity. Most are controlled by PID or linear predictive control methods without considering the complexity. This paper shows that a more comprehensive nonlinear-model-based predictive control method can further improve control performance. A verification of a nonlinear process model with plant data is first shown. Then the design of nonlinear predictive functional control is discussed and results are shown by way of simulations and application to demonstrate the effectiveness and feasibility of the proposed control strategy.

► Step-response plus nonlinear optimization based modeling is presented.
► Corresponding predictive functional control algorithm is presented.
► A recurrence algorithm is presented for closed-loop control performance analysis.