文章基本信息

标题：Adaptive Multi-stage Output Feedback NMPC using the Extended Kalman Filter for time varying uncertainties applied to a CSTR
本地全文：下载
作者：Sankaranarayanan Subramanian ; Sergio Lucia ; Sebastian Engel 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：23
页码：242-247
DOI：10.1016/j.ifacol.2015.11.290
语种：English
出版社：Elsevier
摘要：AbstractNonlinear Model Predictive control (NMPC) is one of the advanced control strategies for multi-dimensional nonlinear systems with constraints. With uncertainties present in the model, robust NMPC strategies are proposed in order to counteract the effects of the uncertainties and have a safe operation of the plant.Multi-stage NMPC offers a non-conservative alternative as it models the feedback information explicitly in the problem formulation by means of a scenario tree. In order to be robust to both the model uncertainties and the estimation error, we formulate a multi-stage output feedback NMPC strategy by creating additional scenarios by sampling the innovations and use observer equations to predict the future evolution of the plant. Since the observers such as the Extended Kalman Filter (EKF) can be used to estimate the uncertain parameters along with the states, the output feedback NMPC strategy is improved to be adaptive with respect to time varying uncertain parameters and the performance of the controller is improved. We demonstrate the advantages of the proposed adaptive scheme using a nonlinear Continuous Stirred Tank Reactor (CSTR) example.
关键词：KeywordsModel-based controlOutput feedback nonlinear model predictive controlAdaptive NMPCExtended Kalman FilterRobust control