| In the actual process control system,the set value target is a common control target,but in many practical cases,the influence of the controlled variable fluctuation in a specific range on product quality is almost the same.For this kind of control system,the controlled variable is not driven to a strict set value,but is limited within a range,which is called interval control.In this case,the economic performance of the product,control effect and social(environmental protection,energy saving and emission reduction)will be more advantageous than set point control.At the same time,most of the controlled objects in the actual industrial process are multi-variable control systems,and the controlled variables of the system have strong coupling,while the interval control can take into account the control effect of each control variable,so it is of great significance to study the interval control algorithm.This paper designs an interval predictive control strategy based on gradual ellipsoid interval under the framework of interval control.The strategy includes the construction of gradual ellipsoid target interval,using rolling constraint condition to replace the global process constraint condition in the response process of the controlled variable from the initial working point to the target interval,and the design strategy of rolling constraint condition and the corresponding optimization method are given.Firstly,this paper gives a basic introduction to model predictive control,introduces the principle of interval control model in the framework of model predictive control,and briefly introduces the design method of interval model predictive control under the above framework.Then the classical tracking model predictive control is extended to an interval model predictive control with a gradual ellipsoid interval control target.Then a mapping method is designed to transform the ellipsoid control target into a unit sphere and generate the ellipsoid target sequence with relaxation.Secondly,the open loop trajectory constraint of the classical model predictive control is extended to the gradual ellipsoid interval constraint so that the closed-loop trajectory of the system can take into account both the performance of the system and the interval control objective.Finally,the control algorithm is simulated by using the model of heavy oil primary distillation column to demonstrate the feasibility and effectiveness of the strategy. |
