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On the interaction between theory experiments and simulation in developing practical learning control algorithms

Richard Longman (2003)

International Journal of Applied Mathematics and Computer Science

Iterative learning control (ILC) develops controllers that iteratively adjust the command to a feedback control system in order to converge to zero tracking error following a specific desired trajectory. Unlike optimal control and other control methods, the iterations are made using the real world in place of a computer model. If desired, the learning process can be conducted both in the time domain during each iteration and in repetitions, making ILC a 2D system. Because ILC iterates with the real...

On the null-controllability of diffusion equations

Gérald Tenenbaum, Marius Tucsnak (2011)

ESAIM: Control, Optimisation and Calculus of Variations

This work studies the null-controllability of a class of abstract parabolic equations. The main contribution in the general case consists in giving a short proof of an abstract version of a sufficient condition for null-controllability which has been proposed by Lebeau and Robbiano. We do not assume that the control operator is admissible. Moreover, we give estimates of the control cost. In the special case of the heat equation in rectangular domains, we provide an alternative way to check...

On the null-controllability of diffusion equations

Gérald Tenenbaum, Marius Tucsnak (2011)

ESAIM: Control, Optimisation and Calculus of Variations

This work studies the null-controllability of a class of abstract parabolic equations. The main contribution in the general case consists in giving a short proof of an abstract version of a sufficient condition for null-controllability which has been proposed by Lebeau and Robbiano. We do not assume that the control operator is admissible. Moreover, we give estimates of the control cost. In the special case of the heat equation in rectangular domains, we provide an alternative way to check...

On the observability of fuzzy second order control systems

Jong Yeoul Park, P. Balasubramaniam, Hyun Min Kim (2003)

Kybernetika

In this paper, the observability of fuzzy logic second order control system is studied from the aspect of fuzzy differential equations. The fuzzy observability in the weak sense is created using the concept of “likelihood” to indicate on which level and along which solution the state is most likely observable. One of the initial state range has been derived with the given input and output. The result generalizes the previous results.

On the optimal continuous decentralized control of non-linear dynamical multivariable systems about the origin.

Manuel de la Sen Parte (1987)

Trabajos de Investigación Operativa

This paper deals with the local (around the equilibrium) optimal decentralized control of autonomous multivariable systems of nonlinearities and couplings between subsystems which can be expressed as power series in the state-space are allowed in the formulation. They only affect for the optimal performance integrals in cubic and higher terms in the norm of the initial conditions of the dynamical differential system. The basic hypothesis which is made is that the system is centrally-stabilizable...

On the Optimal Control of a Class of Time-Delay System

L. Boudjenah, M.F. Khelfi (2010)

Mathematical Modelling of Natural Phenomena

In this work we study the optimal control problem for a class of nonlinear time-delay systems via paratingent equation with delayed argument. We use an equivalence theorem between solutions of differential inclusions with time-delay and solutions of paratingent equations with delayed argument. We study the problem of optimal control which minimizes a certain cost function. To show the existence of optimal control, we use the main topological properties...

On the optimality of a new class of 2D recursive filters

Leopoldo Jetto (1999)

Kybernetika

The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures based on strip...

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