Journal ArticleDOI
Control of large-scale dynamic systems by aggregation
Reads0
Chats0
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
More filters
Proceedings ArticleDOI
Model reduction of discrete interval system using dominant poles retention and direct series expansion method
TL;DR: In this paper, a method for reduction of discrete interval system using Pade approximation is presented, where the numerator is obtained by matching first r time moments of the system and its model.
Proceedings ArticleDOI
Sliding Mode Control Design via Reduced Order Model Approach
TL;DR: In this paper, the design of sliding mode control for the higher-order system via reduced-order model is presented. But it has not been shown that a sliding-mode control designed for the reduced order model gives similar performance for higher order systems.
Journal ArticleDOI
Representation of linear dynamical systems by aggregated models
TL;DR: In this paper the problem of representing high-order linear dynamical systems by reduced models is investigated through the use of an aggregation technique; optimal aggregated models, corresponding to some given deterministic or stochastic input, are obtained by solving a linear matrix equation.
On the selection of states to be retained in a reduced-order model
TL;DR: In this paper, a criterion for selecting the most important states of a high-order system to be retained in a reduced model is proposed, and a procedure for obtaining the reduced model, based on this criterion, is described.
Journal ArticleDOI
Identification and model reduction from impulse response data
TL;DR: In this article, two new algorithms for identification and model reduction of stable linear continuous systems are proposed, based on the weighted impulse response gramians (Agathoklis and Sreeram 1988 b).
References
More filters
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.