In this work we propose a kernel-based robust nonparametric approach to directdata-drivencontrol of linear systems, in the presence of bounded noise affecting the measurements data. First we formulate the problem of...
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In this work we propose a kernel-based robust nonparametric approach to directdata-drivencontrol of linear systems, in the presence of bounded noise affecting the measurements data. First we formulate the problem of designing a controller in order to match the behavior of a given reference model. Then, we design the controller by applying previous results by some of the authors in the field of kernel-based nonparametric error-in-variables identification. Finally, we show the effectiveness of the presented technique by means of two simulation examples. (C) 2018, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
In this paper, we propose a non-iterativedirectdata-drivencontrol approach, such that the controller is directly identified from input/output data without plant identification step. First we formulate the problem o...
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ISBN:
(纸本)9781509059928
In this paper, we propose a non-iterativedirectdata-drivencontrol approach, such that the controller is directly identified from input/output data without plant identification step. First we formulate the problem of designing a controller in order to match the behavior of an assigned reference model in terms of an equivalent set-membership errors-in-variables problem and we define the feasible controller parameter set. Then, we design the controller parameters by applying previous results by the authors in the field of convex relaxation for errors-in-variables identification. Finally, the effectiveness of the presented technique is shown by means of two simulated examples.
In this paper, we propose a non-iterativedirectdata-drivencontrol approach, such that the controller is directly identified from input/output data without plant identification step. First we formulate the problem o...
详细信息
ISBN:
(纸本)9781509045839
In this paper, we propose a non-iterativedirectdata-drivencontrol approach, such that the controller is directly identified from input/output data without plant identification step. First we formulate the problem of designing a controller in order to match the behavior of an assigned reference model in terms of an equivalent set-membership errors-in-variables problem and we define the feasible controller parameter set. Then, we design the controller parameters by applying previous results by the authors in the field of convex relaxation for errors-in-variables identification. Finally, the effectiveness of the presented technique is shown by means of two simulated examples.
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