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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

Uncertainty propagation in Φ related control systems via the Liouville equation

TL;DR: It is shown that a control system abstraction can capture the time evolution of the uncertainty in the original system by an appropriate choice of control input.
Journal ArticleDOI

On the aggregation of interconnected systems

TL;DR: In this article, it was shown that a large scale interconnected system is aggregable if and only if one component of its components is also aggregable in the component connection model framework.
Proceedings ArticleDOI

The Generalized Hessenberg Representation and Near Unobservability in Model Reduction

TL;DR: In this paper, the Generalized Hessenberg Representation (GHR) of a linear time invariant system has been proposed as a model reduction method by identifying weakly observable states, and the result of this unified treatment is a set of guidelines for producing a good reduced order model.
Proceedings ArticleDOI

Structural decomposition approach for large-scale systems

TL;DR: The interconnections of the subsystems are structurally decomposed and the stability of the overall large-scale system is investigated based on the decompositions and the decentralized control design for the interconnected subsystems can be treated as an algebraic problem.
References
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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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