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Showing papers by "Petar V. Kokotovic published in 1981"


Journal ArticleDOI
TL;DR: In this article, finite state continuous time Markov processes with weak interactions are modeled as singularly perturbed systems and aggregates states are obtained using a grouping algorithm, and two-time scale expansions simplify cost equations and lead to decentralized optimization algorithms.
Abstract: Finite state continuous time Markov processes with weak interactions are modeled as singularly perturbed systems. Aggregate states are obtained using a grouping algorithm. Two-time scale expansions simplify cost equations and lead to decentralized optimization algorithms.

195 citations


Journal ArticleDOI
TL;DR: The slow coherency concept is introduced and an algorithm is developed for grouping machines having identical slow motions into areas as discussed by the authors, where the singular perturbation method is used to separate the slow variables which are the area center of inertia variables and the fast variables which describe the intermachine oscillations within the areas.
Abstract: The slow coherency concept is introduced and an algorithm is developed for grouping machines having identical slow motions into areas. The singular perturbation method is used to separate the slow variables which are the area center of inertia variables and the fast variables which describe the intermachine oscillations within the areas. The areas obtained by this method are independent of fault locations. Three types of simulation approximations illustrated on a nonlinear 48 machine system indicate the validity of this algorithm.

154 citations


Journal ArticleDOI
TL;DR: Through a couple of naive examples the control theorists are invited to re-examine the role of modeling in the study of large scale dynamic systems, and it is shown that it is possible to justify one strongly coupled slow core and N weakly coupled fast subsystems.

53 citations


Journal ArticleDOI
TL;DR: In this article, the absolute stability of single-input, single-output (SISO) singularly perturbed systems with a time varying feedback element is examined via the Popov-Kalman-Yakubovich (PKY) lemma.

20 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigated the relationship between coherency, area decomposition and aggregation for a class of models of electromechanical networks, including power system models, and established that coheuracy conditions and a physically meaningful area-aggregate, reproducing a prescribed set of system modes, depend on external connections only.

15 citations


Proceedings ArticleDOI
01 Dec 1981
TL;DR: In this paper, the authors show that the weak observability assumption is crucial, that is when the parasitics are strongly observable the adaptive schemes are no longer robust, and that the addition of a low pass filter at the output makes the parasITics weakly observable and hence guarantees the robustness of the enlarged scheme.
Abstract: In a recent paper we have established that several adaptive schemes are robust with respect to modeling errors consisting of fast parasitics which are weakly observable in the plant output. We now show that the weak observability assumption is crucial, that is when the parasitics are strongly observable the adaptive schemes are no longer robust. However, the addition of a low pass filter at the output makes the parasitics weakly observable and hence guarantees the robustness of the enlarged scheme.

10 citations


Journal ArticleDOI
TL;DR: In this paper, the authors employ singular perturbation to model and analyze the interaction of sensor-actuator dynamics with the fast modes created by high feedback gain in a feedback system.

1 citations


Proceedings ArticleDOI
01 Dec 1981
TL;DR: In this article, a unified treatment of aggregability, lumpability, coherency and similar properties allowing model simplification is presented, where each of the N groups of states is represented by one aggregate variable and an aggregate model is formed.
Abstract: This paper presents a unified treatment of aggregability, lumpability, coherency and similar properties allowing model simplification. Each of the N groups of states is represented by one aggregate variable and an aggregate model is formed. Interpretation is given when groups are coherent, but not aggregable and vice-versa. In a class of systems aggregability and coherency hold simultaneously.

1 citations