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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Suboptimal Control of Large Scale Systems by Chained Aggregation
TL;DR: In this article, a new procedure to evaluate chained aggregation matrix has been developed using Pouth Canonical form, this method is simple compared to generalized Hessenberg representation and it gives better results when compared to the suboptimal regulators derived using Routh approximant reduced order models.
Framing controllers applying padé approximation technique
Vijaya Yaduvanshi,Vartika Rao +1 more
Abstract: This brief presents a method to commence a reduced order system for a given SISO (stable) linear continuous time system. This approach is about to retain the stability while converting the higher order system into its lower order approximant using Pade approximant and then a controller is put together in the reduced order system attaining stability and necessary parameters of the system. A numerical example is also presented to illustrate the behavior of the original system with its reduced order approximation and then attaching a controller and check the stability of the reduced order system with controller.
Journal ArticleDOI
Planning and forecasting with robust dynamic models
TL;DR: The theorem of representation is applied in order to obtain a family of crisp models for dynamic models formulated with linguistic variables, particularly suitable for dynamic linear programming models, where the coefficients are fuzzy sets or fuzzy numbers.
Peer Review
Application of lqg balanced truncation algorithm to the digital filter design problem - part 2: model order reduction
TL;DR: In this article , a method to use model reduction algorithm to design low-order digital filters was presented, where the LQG balanced truncation algorithm was used to reduce the order of the high-order high order digital filter.
Proceedings ArticleDOI
On a model reduction for linear systems via design parameter retainment
T. Ohse,T. Kunitomi +1 more
TL;DR: In this paper, a method for model reduction preserving design specification parameters for a class of linear dynamic systems is described, where the structure of the original model is shown, and a lower-order model retaining the specification parameters is proposed.
References
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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.
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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.