NDLI: Constrained nonlinear predictive control using Volterra models

Content Provider	IEEE Xplore Digital Library
Author	Dorado, F. Bordons, C.
Copyright Year	2005
Description	Author affiliation: Univ. de Sevilla (Dorado, F.; Bordons, C.)
Abstract	This paper presents a constrained model predictive control strategy that can be used to control nonlinear processes described by Volterra models. The controller exploits the special structure of the model to achieve an online feasible solution to the general optimization problem. Efficient solutions can be found, especially for second order Volterra models, that can solve the nonlinear problem by iteration of the linear solution, based on the particular structure of the model. This iterative procedure makes use of an analytical solution in the unconstrained case or a QP solution if constraints exist allowing an easy solution to the nonlinear problem. The complexity is therefore reduced compared to the computations needed to solve the general constrained non-linear optimization by a non-linear programming (NLP) technique. The procedure is tested on a simulated non-linear continuous stirred reactor and compared to other nonlinear MPC strategies both in complexity and computation time, showing that the proposed structure is a good candidate for a great class of industrial processes
Starting Page	7
Ending Page	1013
File Size	2670719
Page Count	1007
File Format	PDF
ISBN	0780394011
DOI	10.1109/ETFA.2005.1612782
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-19
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive control Predictive models Industrial control Process control Quadratic programming Testing Computer industry Cost function Constraint optimization Computational modeling
Content Type	Text
Resource Type	Article

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