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This work was supported in part by the grant PID2021-124908NB-I00 founded by MCIN/AEI/10.13039/501100011033/ and by ''ERDF A way of making Europe''; by the Universitat Politecnica de Valencia through the grant SP20200109 (PAID-10-20); by grant PRE2019-087579 funded by MCIN/AEI/10.13039/501100011033 and by ''ESF Investing in your future''; and by the Generalitat Valenciana regional government through project CIAICO/2021/064. Funding for open access charge: CRUE-Universitat Politecnica de Valencia.

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Advantages of using relevant nearly optimal solutions in multi-objective tuning of robust controllers

Publicado en:Isa Transactions. 139 143-155 - 2023-08-16 139(), DOI: 10.1016/j.isatra.2023.05.003

Autores: Pajares, Alberto; Blasco, Xavier; Herrero, Juan Manuel; Veyna, Uriel

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This paper presents a new approach for the multiobjective optimal design of robust controllers in systems with stochastic parametric uncertainty. Traditionally, uncertainty is incorporated into the optimization process. However, this can generate two problems: (1) low performance in the nominal scenario; and (2) high computational cost. For the first point, it is possible to ensure that the controllers produce an acceptable performance for the nominal scenario in exchange for being lightly robust. For the second point, the methodology proposed in this work reduces the computational cost significantly. This approach addresses uncertainty by analyzing the robustness of optimal and nearly optimal controllers in the nominal scenario. The methodology guarantees obtaining controllers that are similar/neighboring to lightly robust controllers. Two examples of controller design are shown: one for a linear model and another for a nonlinear model. Both examples demonstrate the usefulness of the proposed new approach.& COPY; 2023 The Author(s). Published by Elsevier Ltd on behalf of ISA. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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