The Integration Of Process Design And Control Based On Robust Modeling Approach

Traditionally,chemical processes are designed using sequential approach.First,based on the steady-state model and cost optimality criteria,the optimization design variables are obtained.Subsequently,based on the designed process,the corresponding manipulated variables,controlled variables and control strategies are designed to meet the requirements of dynamic control performance.This approach might reduce calculation complexity,but ignores the inherent relationship between process design and process control.The designed processes based on steady-state optimization may not match the corresponding controllers very well.The dynamic performance is poor especially for some strong nonlinear processes.Due to limits of sequential design,many scholars have gradually focused on the field of integration of process design and control.A large number of researches have showed that integration of process design and control can obtain better economic performance and dynamic performance for chemical processes.In this paper,some approaches are presented for the integration of process design and control and are applied to the CSTR processes.The main work of this paper is as follows:(1)The state-of-the-art of the integration of process design and control was surveyed from three aspects:(I)The scope of the research;(II)Treatment methods of external disturbances and uncertainties;(III)The solution algorithm.In addition,robust model theory was introduced.(2)A robust modeling-based approach was utilized for the integration of process design and control with application to CSTR processes.The key idea of the presented approach was that the system’s closed-loop dynamic behavior was represented as a nominal linear state space model with uncertain model parameters.Then,the obtained robust model and a quadratic Lyapunov function were used to compute a bound of the worst-case scenario,at the same time,process stability and process feasibility could also be guaranteed.Finally,the presented method was compared to the dynamic optimization-based method.The results showed the proposed method could ensure the economy and dynamic performance,as well as the robust stability for the designed process.(3)It is a fact that the hierarchical control structure has been used widely inchemical process.Advanced control is a kind of multi-variable control based on the model,which can optimize the operation point of the process,and the conventional PID controller has the advantages of quick response and easy operation.Therefore,based on the previous work,an integrated approach using hierarchical control structure was proposed for the integration of process design and control.Specifically,a hierarchical LQR-PI control strategy was introduced into the integrated design framework to improve the dynamic performance.Moreover,conservatism can be reduced further..Firstly,the controlled process and the conventional PI controller are used as the controlled object of the advanced control layer,and a hierarchical control structure of LQR-PI is constructed.Then,under the presence of external time-varying disturbance and parameter uncertainties,a robust model was obtained by identifying the closed-loop process that consists of LQR controller and general object.Finally,the optimal process design and controller parameters are obtained by solving a nonlinear programming problem.The effectiveness of the proposed method was illustrated through the CSTR process and is compared to the previous design results.