NDLI: Control horizon estimation of input constrained MPC based on control saturation

Content Provider	IEEE Xplore Digital Library
Author	Sun Yong Zhang Maorui Zhang Ze
Copyright Year	2011
Description	Author affiliation: Center for Control Theory and Guidance Technology, Harbin Institute of Technology, 150001, China (Sun Yong; Zhang Maorui; Zhang Ze)
Abstract	This paper gives two new algorithms for estimating the upper bound of the control horizon for input constrained model predictive control (MPC) problem based on the input saturation and the K-step null-controllable region. The input saturation must occur at one time, which is considered in estimating the control horizon. The state within the polytope can be expressed by a convex combination of the vertices of one facet of the polytope and these vertices are considered to compute the global upper bound. The proposed algorithms are compared with others by an example and the results show that the methods of this paper have the less conservative estimation of the control horizon.
Starting Page	3377
Ending Page	3382
File Size	154105
Page Count	6
File Format	PDF
ISBN	9781457706776
ISSN	21612927
e-ISBN	9789881725592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Constrained Linear Quadratic Regulation Control Horizon Upper bound Optimal control Predictive models Eigenvalues and eigenfunctions Trajectory Constrained Finite Horizon Quadratic programming Model Predictive Control Predictive control
Content Type	Text
Resource Type	Article

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