State-Feedback, Finite-Horizon, Cost Density-Shaping Control for the Linear Quadratic Gaussian Framework

A Multiple-Cumulant Cost Density-Shaping (MCCDS) control is proposed for the case when the system is linear and the cost is quadratic. This linear optimal control results from the minimization of an analytic, convex, non-negative function of cost cumulants and target cost cumulants. The MCCDS contro...

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Bibliographic Details
Published in:Journal of optimization theory and applications 2011-08, Vol.150 (2), p.251-274
Main Authors: Zyskowski, M. J., Sain, M. K., Diersing, R. W.
Format: Article
Language:English
Subjects:
Acceleration
Applications of Mathematics
Applied sciences
Calculus of Variations and Optimal Control
Optimization
Cost analysis
Cost engineering
Density
Designers
Drift
Dynamic programming
Engineering
Exact sciences and technology
Mathematical analysis
Mathematical programming
Mathematics
Mathematics and Statistics
Operational research and scientific management
Operational research. Management science
Operations Research/Decision Theory
Optimization
Random variables
Seismic phenomena
Studies
Theory of Computation
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Summary:A Multiple-Cumulant Cost Density-Shaping (MCCDS) control is proposed for the case when the system is linear and the cost is quadratic. This linear optimal control results from the minimization of an analytic, convex, non-negative function of cost cumulants and target cost cumulants. The MCCDS control allows the designer to shape the initial cost density with respect to a target density approximated by target cost cumulants. A numerical experiment shows that MCCDS control compares favorably with competing control paradigms in terms of official performance measures for inter-story drifts and per-story accelerations used in the first-generation structure benchmark for seismically excited buildings.
ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-011-9836-0