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Canonical input-output representation of linear multivariable stochastic systems and joint optimal parameter and state estimation.

G. Salut, J. Aguilar-Martín, S. Lefevre (1979)

Stochastica

In this paper a complete presentation is given of a new canonical representation of multi-input, multi-output linear stochastic systems. Its equivalence with operator form directly linked with ARMA processes as well as with classical state space representation is given, and a transfer matrix interpretation is developed in an example. The importance of the new representation is mainly in the fact that in the joint state and parameters estimation problem, all unknown parameters appear linearly when...

Comparison principle approach to utility maximization

Peter Imkeller, Victor Nzengang (2015)

Banach Center Publications

We consider the problem of optimal investment for maximal expected utility in an incomplete market with trading strategies subject to closed constraints. Under the assumption that the underlying utility function has constant sign, we employ the comparison principle for BSDEs to construct a family of supermartingales leading to a necessary and sufficient condition for optimality. As a consequence, the value function is characterized as the initial value of a BSDE with Lipschitz growth.

Completitud esencial de la clase de controles basados en un proceso suficiente.

Pilar Ibarrola Muñoz, Javier Yáñez Gestoso (1985)

Trabajos de Estadística e Investigación Operativa

Se define en este artículo el concepto de proceso suficiente para un proceso de control, así como el de control basado en un proceso suficiente. Se demuestra a continuación que el conjunto de controles basados en un proceso suficiente forma una clase esencialmente completa; por consiguiente, dado un control, existe un control basado en el proceso suficiente que tiene el mismo coste esperado que el anterior.

Constrained controllability of nonlinear stochastic impulsive systems

Shanmugasundaram Karthikeyan, Krishnan Balachandran (2011)

International Journal of Applied Mathematics and Computer Science

This paper is concerned with complete controllability of a class of nonlinear stochastic systems involving impulsive effects in a finite time interval by means of controls whose initial and final values can be assigned in advance. The result is achieved by using a fixed-point argument.

Controllability of nonlinear impulsive Ito type stochastic systems

Rathinasamy Sakthivel (2009)

International Journal of Applied Mathematics and Computer Science

In this article, we consider finite dimensional dynamical control systems described by nonlinear impulsive Ito type stochastic integrodifferential equations. Necessary and sufficient conditions for complete controllability of nonlinear impulsive stochastic systems are formulated and proved under the natural assumption that the corresponding linear system is appropriately controllable. A fixed point approach is employed for achieving the required result.

Controllability of nonlinear stochastic systems with multiple time-varying delays in control

Shanmugasundaram Karthikeyan, Krishnan Balachandran, Murugesan Sathya (2015)

International Journal of Applied Mathematics and Computer Science

This paper is concerned with the problem of controllability of semi-linear stochastic systems with time varying multiple delays in control in finite dimensional spaces. Sufficient conditions are established for the relative controllability of semilinear stochastic systems by using the Banach fixed point theorem. A numerical example is given to illustrate the application of the theoretical results. Some important comments are also presented on existing results for the stochastic controllability of...

Controllability of semilinear stochastic integrodifferential systems

Krishnan Balachandran, S. Karthikeyan, Jeong-Hoon Kim (2007)

Kybernetika

In this paper we study the approximate and complete controllability of stochastic integrodifferential system in finite dimensional spaces. Sufficient conditions are established for each of these types of controllability. The results are obtained by using the Picard iteration technique.

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