3,072 research outputs found

    Decoupling and iterative approaches to the control of discrete linear repetitive processes

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    This paper reports new results on the analysis and control of discrete linear repetitive processes which are a distinct class of 2D discrete linear systems of both systems theoretic and applications interest. In particular, we first propose an extension to the basic state-space model to include a coupling term previously neglected but which arises in some applications and then proceed to show how computationally efficient control laws can be designed for this new model

    <i>H</i><sub>2</sub> and mixed <i>H</i><sub>2</sub>/<i>H</i><sub>āˆž</sub> Stabilization and Disturbance Attenuation for Differential Linear Repetitive Processes

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    Repetitive processes are a distinct class of two-dimensional systems (i.e., information propagation in two independent directions) of both systems theoretic and applications interest. A systems theory for them cannot be obtained by direct extension of existing techniques from standard (termed 1-D here) or, in many cases, two-dimensional (2-D) systems theory. Here, we give new results towards the development of such a theory in H2 and mixed H2/Hāˆž settings. These results are for the sub-class of so-called differential linear repetitive processes and focus on the fundamental problems of stabilization and disturbance attenuation

    An Innovative MIMO Iterative Learning Control Approach for the Position Control of a Hydraulic Press

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    To improve the performance of hydraulic press position control and eliminate the need to manually define control signals, this paper proposes a multi-input-multi-output (MIMO) Iterative Learning Control (ILC) algorithm. The MIMO ILC algorithm design is based on the inversion of the known low frequency dynamics of the hydraulic press, whereas the unknown and uncertain high frequency dynamics are discarded due to their low influence in the learning transient. Moreover, for the MIMO ILC convergence condition, a graphical method is proposed, in which the ILC learning filter eigenvalues are analyzed. This method allows studying the stability and convergence rate of the algorithm intuitively. Theoretical analysis and results prove that with the MIMO ILC algorithm the position control is automated and that high precision in the position tracking is gained. A comparison with other model inverse ILC approaches is carried out and it is shown that the proposed MIMO ILC algorithm outperforms the existing algorithms, reducing the number of iterations required to converge while guaranteeing system stability. Furthermore, experimental results in a hydraulic test rig are presented and compared to those obtained with a conventional PI controllerThis work was supported in part by the Department of Development and Infrastructures of the Government of the Basque Country via Industrial Doctorate Program BIKAINTEK under Grant 20-AF-W2-2018-00015

    Feedforward control for lightweight motion systems

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    Analog, hybrid, and digital simulation

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    Analog, hybrid, and digital computerized simulation technique
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