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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

Robust topology optimization based on an aggregated linear system and eigenvalue analysis

TL;DR: The proposed robust structural optimization method is implemented using the topology optimization method, sensitivity analysis and the method of moving asymptotes (MMA) to establish the worst load cases corresponding to these optimal structures.
Proceedings ArticleDOI

Aggregation-based model reduction for tokamak control

TL;DR: In this article, the use of model reduction schemes based on eigenstructure analysis is shown to be useful in the study of control problems in tokamak experiments, and state aggregation techniques allow to produce reduced-order models where the physical meaning of the state variables is preserved.

Suboptimal Decentralized Control of Multivariable Systems

TL;DR: In this paper, a state-space design for multivariable, sub-optimal decentralized control is presented, which is based upon the scalar multiplier with a cost function βJ *.
Proceedings ArticleDOI

Reduced order modeling of electrical circuits: Simulation and hardware validation

TL;DR: A well-known truncation method is adopted to reduce the order of original system and the scheme is implemented for electrical circuits, showing response of original model and reduced order model matches.
References
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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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