Data processing: artificial intelligence – Adaptive system
Reexamination Certificate
2007-03-27
2007-03-27
Hirl, Joseph P (Department: 2129)
Data processing: artificial intelligence
Adaptive system
C706S012000, C706S046000
Reexamination Certificate
active
10620569
ABSTRACT:
An efficient method for solving a model predictive control problem is described. A large sparse matrix equation is formed based upon the model predictive control problem. The square root of H, Hr, is then formed directly, without first forming H. A square root (LSMroot) of a large sparse matrix of the large sparse matrix equation is then formed using Hr in each of a plurality of iterations of a quadratic programming solver, without first forming the large sparse matrix and without recalculating Hr in each of the plurality of iterations. The solution of the large sparse matrix equation is completed based upon LSMroot.
REFERENCES:
patent: 5654907 (1997-08-01), Lange
patent: 6064809 (2000-05-01), Braatz et al.
patent: 7152023 (2006-12-01), Das
patent: 2004/0107012 (2004-06-01), Das et al.
patent: 2004/0162709 (2004-08-01), Das
patent: WO 01/79945 (2001-10-01), None
T. A. Driscoll et al, Computational Efficiency of a Functional Expansion Algorithm for Linear Quadratic Optimal Control, 1992, IEEE, CH3229-2/92/0000-0143, 143, 144.
Matthew J. Tenny, Nonlinear Model Predictive Control via Feasibility-Perturbed Sequential Quadratic Programming, 2002, University of Wisconsin, 1-29.
Edward Rothberg, Techniques for Improving the Performance of Sparse Matrix Factorization on Multiprocessor Workstations, IEEE, CH2916-5/90/0000/0232, 232-241.
Christopher V. Rao et al, Application of Interior-Point Methods to Model Predictive Control, Argonne National Laboratory, 1-31.
Gene H. Golub, Charles F. Van Loan, Matrix Computations Third Edition, pp. 210-211 & 224-225.
Thomas Kailath, Linear Systems, pp. 248-253, Prentice-Hall Inc., Englewood Cliffs, NJ.
Christopher V. Rao, Stephen J. Wright, James B. Rawlings, Application of Interior-Point Methods to Model Predictive Control, Mathematics and Computer Science Division Argonne National Laboratory pp. 1-31.
Search Rpt. EP04254226.
Rothberg E et al.: “Techniques for improving the performance of sparse matrix factorization on multiprocessor workstations”, Proceedings of the supercomputing conference. New York Nov. 12-16, 1990 Washington IEEE comn. Soc. Press US vol. Conf 3.
Nov. 12, 1990, pp. 232-241, XP0100019944. ISBN: 0-8181-2056-0 *the whole document*.
Driscoll T A et al.: “Computational efficiency of a functional expansion algorithm for linear quadratic optimal control” Proceedings of the conference on decision and control. Tucson, Dec. 16, vol. 3 Conf. 31, Dec. 16, 1992, pp. 143-144, XP010108119.
ISBN: 0-7803-0872-7 *the whole document*.
Carlson & Gaskey & Olds
United Technologies Corporation
LandOfFree
Square root method for computationally efficient model... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Square root method for computationally efficient model..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Square root method for computationally efficient model... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3745491