Displaying similar documents to “On the interaction between theory experiments and simulation in developing practical learning control algorithms”

Motor control neural models and systems theory

Kenji Doya, Hidenori Kimura, Aiko Miyamura (2001)

International Journal of Applied Mathematics and Computer Science

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In this paper, we introduce several system theoretic problems brought forward by recent studies on neural models of motor control. We focus our attention on three topics: (i) the cerebellum and adaptive control, (ii) reinforcement learning and the basal ganglia, and (iii) modular control with multiple models. We discuss these subjects from both neuroscience and systems theory viewpoints with the aim of promoting interplay between the two research communities.

Iterative Learning Control - monotonicity and optimization

David H. Owens, Steve Daley (2008)

International Journal of Applied Mathematics and Computer Science

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The area if Iterative Learning Control (ILC) has great potential for applications to systems with a naturally repetitive action where the transfer of data from repetition (trial or iteration) can lead to substantial improvements in tracking performance. There are several serious issues arising from the "2D" structure of ILC and a number of new problems requiring new ways of thinking and design. This paper introduces some of these issues from the point of view of the research group at...

An example of the knowledge based controller-design and evaluation.

Oto Tezak (1999)

Mathware and Soft Computing

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Knowledge based controller for a balance control model is presented in this paper. The design of the controller was based on the human control of the same process. Developed controller is tested by means of simulation and operation on the laboratory balance control model. The simulation results of the controller as well as a statistical description of the experiments with developed controller and human control is presented in the paper. Verification is based on experiments with an intelligent...

A comparison of two FEM-based methods for the solution of the nonlinear output regulation problem

Branislav Rehák, Sergej Čelikovský, Javier Ruiz, Jorge Orozco-Mora (2009)

Kybernetika

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The regulator equation is the fundamental equation whose solution must be found in order to solve the output regulation problem. It is a system of first-order partial differential equations (PDE) combined with an algebraic equation. The classical approach to its solution is to use the Taylor series with undetermined coefficients. In this contribution, another path is followed: the equation is solved using the finite-element method which is, nevertheless, suitable to solve PDE part only....

A variable structure observer for the control of robot manipulators

Abdelkader Abdessameud, Mohamed Khelfi (2006)

International Journal of Applied Mathematics and Computer Science

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This paper deals with the application of a variable structure observer developed for a class of nonlinear systems to solve the trajectory tracking problem for rigid robot manipulators. The analyzed approach to observer design proposes a simple design methodology for systems having completely observable linear parts and bounded nonlinearities andor uncertainties. This observer is basically the conventional Luenberger observer with an additional switching term that is used to guarantee...

Finite-time tracking control of multiple nonholonomic mobile robots with external disturbances

Meiying Ou, Shengwei Gu, Xianbing Wang, Kexiu Dong (2015)

Kybernetika

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This paper investigates finite-time tracking control problem of multiple nonholonomic mobile robots in dynamic model with external disturbances, where a kind of finite-time disturbance observer (FTDO) is introduced to estimate the external disturbances for each mobile robot. First of all, the resulting tracking error dynamic is transformed into two subsystems, i. e., a third-order subsystem and a second-order subsystem for each mobile robot. Then, the two subsystem are discussed respectively,...

Iterative learning control for over-determined under-determined, and ill-conditioned systems

Konstantin Avrachenkov, Richard Longman (2003)

International Journal of Applied Mathematics and Computer Science

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This paper studies iterative learning control (ILC) for under-determined and over-determined systems, i.e., systems for which the control action to produce the desired output is not unique, or for which exact tracking of the desired trajectory is not feasible. For both cases we recommend the use of the pseudoinverse or its approximation as a learning operator. The Tikhonov regularization technique is discussed for computing the pseudoinverse to handle numerical instability. It is shown...