基于鲁棒模型与分层递阶控制的工艺与控制系统集成设计研究

Integration of process design and control based on robust modeling and hierarchical control structure

化工过程工艺与控制系统的集成设计研究越来越受到国内外工艺设计和过程控制领域研究人员的重视,与传统的分步序贯设计相比,集成设计可获得经济性能和动态性能更优的化工过程。考虑到工业过程中广泛采用先进控制与常规控制分层递阶控制结构,提出了一种基于鲁棒模型和分层递阶控制策略的过程工艺与控制系统集成设计方法。其核心思想是将设计对象和常规控制器构成广义对象,通过辨识得到先进控制与广义对象组成的闭环过程状态空间不确定模型,基于该模型以及二次李雅普诺夫函数可估计所设计工艺过程在外部扰动作用下的最坏情况。该方法将集成设计问题转化成一个非线性规划问题,避免了求解集成优化问题常用的动态优化方法,并最终得到经济性能和动态性能良好的工艺设计参数与控制器参数。案例研究证明了方法的可行性。

In recent years, integration of process design and control （IPDC） for chemical processes have received increasing attention from researchers in process design and process control field. IPDC can obtain better economic performance and dynamic performance for chemical processes when compared to traditional sequent design method. In addition, it is a fact that the hierarchical control structure has been used widely in industrial processes. Therefore, an approach based on hierarchical control structure was proposed for the IPDC using robust modeling method. Firstly, the generalized object was achieved based on the designed process and conventional PID controllers. Secondly, the closed-loop linear state space model with uncertain model parameters was obtained by system identification method. Thirdly, the obtained robust model and a quadratic Lyapunov function were used to compute a bound of the worst-case scenario, process stability and process feasibility. This method based on robust modeling avoided the solution of dynamic optimization, which is usually adopted in the integration of process design and control. Finally, the case study demonstrated that the presented method was feasible for IPDC of chemical processes.