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Control of large-scale dynamic systems by aggregation

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TLDR
Using the quantitative definition of weak coupling proposed by Milne, a suboptimal control policy for the weakly coupled system is derived and questions of performance degradation and of stability of such suboptimally controlled systems are answered.
Abstract
A method is proposed to obtain a model of a dynamic system with a state vector of high dimension. The model is derived by "aggregating" the original system state vector into a lower-dimensional vector. Some properties of the aggregation method are investigated in the paper. The concept of aggregation, a generalization of that of projection, is related to that of state vector partition and is useful not only in building a model of reduced dimension, but also in unifying several topics in the control theory such as regulators with incomplete state feedback, characteristic value computations, model controls, and bounds on the solution of the matrix Riccati equations, etc. Using the quantitative definition of weak coupling proposed by Milne, a suboptimal control policy for the weakly coupled system is derived. Questions of performance degradation and of stability of such suboptimally controlled systems are also answered in the paper.

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Citations
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Journal ArticleDOI

A design technique for the incomplete state feedback problem in multivariable control systems

TL;DR: The problem of choosing the ''best'' state variables to measure from a set of measurable state variables in a linear, time-invariant multivariable system with linear time- Invariant incomplete state feedback is considered and an extension of Rosenbrock's Modal Analysis Technique is used.
Journal ArticleDOI

The adjoint method coupled with the modal identification method for nonlinear model reduction

TL;DR: In this article, the modal identification method (MIM) was used with the Finite Difference Method (FDM) for the computation of the gradient of the functional to be minimized.
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An algorithm for the computer simulation of very large dynamic systems

Edward J. Davison
- 01 Nov 1973 - 
TL;DR: The proposed algorithm has a truncation error of 0(h"5) where h is the step-size, is numerically stable for any h provided the original system is stable and the Lipschitz constant is small enough, and will give exact steady-state solutions for constant input systems for anyh.
Journal ArticleDOI

Canonical forms for aggregated models

TL;DR: In this article, it is shown that starting with canonical forms of linear multivariable systems, it is possible to obtain an aggregated reduced-order model which retains the same structure as the original canonical form but with smaller blocks.
Journal ArticleDOI

Control theory and economic policy: Balance and perspectives

TL;DR: A selection of applications of control theory to the analysis of economic policy problems, including deterministic, stochastic and decentralized optimum control, and promising areas of mutual cooperation between control theorists and economists are identified.
References
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R. E. Kalman
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On "A method for simplifying linear dynamic systems"

TL;DR: A method is proposed for reducing large matrices by constructing a matrix of lower order which has the same dominant eigenvalues and eigenvectors as the original system.
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Estimation of the state vector of a linear stochastic system with a constrained estimator

TL;DR: In this article, a constructive design procedure for the problem of estimating the state vector of a discrete-time linear stochastic system with time-invariant dynamics when certain constraints are imposed on the number of memory elements of the estimator is presented.
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