Linear Model Predictive Control (MPC) can be considered as the state of the art advanced process control technology in model-based automation of continuous chemical processes. For (semi-)batch processes, that often present a strongly nonlinear (or even unstable) behavior in combination with fast dynamics, Nonlinear Model Predictive Control (NMPC) is a more suited technology. However, online applications of NMPC have a hard time to penetrate in industry despite methodological developments, tools and examples in academia. In this paper, we propose a roadmap to argue against the intrinsic reasons and practical limitations that slow down the practical online applications of NMPC. This roadmap is applied to an existing semi-batch plant as a practical case study. The results have shown that the NMPC algorithm can provide an improved control, namely a better tracking of the main process variables, a reduction in the reaction time, and robustness with respect to model-plant mismatch and disturbances.

在连续化学过程的基于模型的自动化中，线性模型预测控制（MPC）可被视为最先进的先进过程控制技术。对于（半）批生产过程，通常结合快速动力学表现出强烈的非线性（甚至不稳定）行为，非线性模型预测控制（NMPC）是更合适的技术。然而，尽管在学术界有方法学方面的发展，工具和实例，但NMPC的在线应用程序很难渗透到行业中。在本文中，我们提出了一个路线图，以反对减慢NMPC的实际在线应用程序的内在原因和实际限制。将此路线图应用到现有的半间歇式工厂中，作为一个实际案例研究。结果表明，NMPC算法可以提供改进的控制，