NDLI: Infinite-horizon model predictive control with structured input signals

Content Provider	IEEE Xplore Digital Library
Author	van den Boom, T.J.J.
Copyright Year	2002
Description	Author affiliation: Dept. of Inf. Technol. & Syst., Delft Univ. of Technol., Netherlands (van den Boom, T.J.J.)
Abstract	Model predictive control (MPC) is a very popular controller design method in the process industry. One of the main advantages of MPC is that it can handle constraints on the inputs and outputs and it is capable of tracking pre-scheduled reference signals. In the paper the infinite prediction horizon problem is discussed. The input signal has been structured, in order to be able to handle signal constraints, to track pre-scheduled reference signals and to reject measurable disturbances. Beyond a switching horizon, the input signal is described by a number of (orthogonal) basis functions or a static state feedback. By structuring the input, the degrees of freedom in the resulting optimization problem remains bounded. The optimal infinite-horizon model predictive control-law is given in a closed form. In the unconstrained case an expression for the LTI controller is derived.
Sponsorship	American Autom. Control Council IFAC SICE
Starting Page	448
Ending Page	453
File Size	325184
Page Count	6
File Format	PDF
ISBN	0780372980
ISSN	07431619
DOI	10.1109/ACC.2002.1024846
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-05-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Predictive models Predictive control State feedback Optimal control Electrical equipment industry Industrial control Stability Control engineering Information technology Design methodology
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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