Journal ArticleDOI
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.read more
Citations
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Aggregation of many coupled consecutive first order reactions
Sudhir V. Golikeri,Dan Luss +1 more
TL;DR: In this paper, the behavior of a mixture in which many coupled irreversible consecutive first order reactions occur is investigated and the errors involved in representing it as a pseudo ternary system are examined.
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Optimal chained aggregation for reduced-order modeling†
TL;DR: In this article, a theory is proposed for a new optimal process to perform chained aggregation in reduced-order modelling, where almost invariant subspaces and approximate aggregation are introduced.
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Model Order Reduction of Interval Systems using Mihailov Criterion and Factor Division Method
TL;DR: A mixed method for reducing order of the large scale interval systems using the Mihailov Criterion and factor division method to guarantee the stability of the reduced model if the original system is stable.
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Tackling continuous state-space explosion in a Markovian process algebra
TL;DR: This paper studies the case when the replicated objects are best described as composites which consist of smaller simple objects, and simplifies the potentially massive ODE system arising in those circumstances to one whose size is independent from all the multiplicities in the model.
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Aggregation matrix for the reduced-order continued fraction expansion model of Chen and Shieh
TL;DR: A relationship between the states of a high-order system and its reduced-order continued fraction expansion model of Chen and Shieh has been derived in this paper, in the form of an aggregation matrix.
References
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Journal ArticleDOI
Decomposition Principle for Linear Programs
George B. Dantzig,Philip Wolfe +1 more
TL;DR: A technique is presented for the decomposition of a linear program that permits the problem to be solved by alternate solutions of linear sub-programs representing its several parts and a coordinating program that is obtained from the parts by linear transformations.
Contributions to the theory of optimal control
TL;DR: In this article, the authors considered the problem of least square feedback control in a linear time-invariant system with n states, and proposed a solution based on the concept of controllability.
Journal ArticleDOI
On "A method for simplifying linear dynamic systems"
M. Chidambara,Edward J. Davison +1 more
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.
Journal ArticleDOI
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.