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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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Automatic construction of a simplified burn-up chain model by the singular value decomposition

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Modeling of linear time-varying systems by linear time-invariant systems of lower order

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A bibliographical survey of large-scale systems

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Decentralized two-level excitation control of multimachine power systems

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New approach of Gerschgorin theorem in model order reduction

TL;DR: In this paper, a simple approach is proposed for model order reduction of state space system based on a new approach of Gerschgorin theorem and singular perturbation technique, which can identify the location of dominant and non-dominant eigenvalues of a system.
References
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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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