Conference Paper

Nonlinear predictive control for real time applications

Ind. Control Centre, Strathclyde Univ., Glasgow
DOI: 10.1109/CACSD-CCA-ISIC.2006.4776648 In proceeding of: Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
Source: IEEE Xplore

ABSTRACT The design of nonlinear predictive controllers based on linear time-varying prediction models is discussed. The linear time-varying models can be obtained by applying a local linearization along the nominal input and state trajectory or by describing the nonlinear state equations by state dependent state space equations. A graphical predictive control framework that provides practical methods for nonlinear control design is introduced using LabVIEW. The effectiveness of the algorithms and the easy applicability of the developed framework are illustrated in a simulation example

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    ABSTRACT: This paper provides an overview of commercially available Model Predictive Control (MPC) technology, based primarily on data provided by MPC vendors. A brief history of industrial MPC technology is presented first, followed by results of our vendor survey of MPC control and identification technology. A general MPC control algorithm is presented, and approaches taken by each vendor for the different aspects of the calculation are described. Identification technology is then reviewed to determine similarities and differences between the various approaches. MPC applications performed by each vendor are summarized by application area. The final section presents a vision of the next generation of MPC technology, with an emphasis on potential business and research opportunities. Keywords Industrial Survey, Model Predictive Control Introduction Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulated variable adjustments in order to optimize the...