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dc.contributor.authorAzar, Ahmad Taher
dc.contributor.authorAbed, Azher M.
dc.contributor.authorAbdul-Majeed, Farah Ayad
dc.contributor.authorHameed, Ibrahim A.
dc.contributor.authorJawad, Anwar Ja’afar Mohamad
dc.contributor.authorAbdul-Adheem, Wameedh Riyadh
dc.contributor.authorIbraheem, Ibraheem Kasim
dc.contributor.authorKamal, Nashwa Ahmad
dc.date.accessioned2023-10-27T12:28:58Z
dc.date.available2023-10-27T12:28:58Z
dc.date.created2023-05-22T12:58:04Z
dc.date.issued2023
dc.identifier.citationMachines. 2023, 11 (4), .en_US
dc.identifier.urihttps://hdl.handle.net/11250/3099183
dc.description.abstractThis paper presents a novel extended state observer (ESO) approach for a class of plants with nonlinear dynamics. The proposed observer estimates both the state variables and the total disturbance, which includes both exogenous and endogenous disturbance. The study’s changes can be summarized by developing a sliding mode higher-order extended state observer with a higher-order augmented state and a nonlinear function for the estimation error correction terms (SMHOESO). By including multiple enhanced states, the proposed observer can monitor total disturbances asymptotically, with the second derivative of the total disturbance serving as an upper constraint on the estimation error. This feature improves the observer’s ability to estimate higher-order disturbances and uncertainty. To extend the concept of the linear extended state observer (LESO), a nonlinear function can modify the estimation error in such a way that the proposed observer can provide faster and more accurate estimations of the state and total disturbance. The proposed nonlinearity also reduces the chattering issue with LESOs. This research thoroughly examines and analyzes the proposed SMHOESO’s convergence using the Lyapunov technique. According to this analysis, the SMHOESO is asymptotically stable, and the estimation error can be significantly reduced under real-world conditions. In addition to the SMHOESO, a modified Active Disturbance Rejection Control (ADRC) scheme is built, which includes a nonlinear state error feedback (NLSEF) controller and a nonlinear tracking differentiator (TD). Several nonlinear models, including the Differential Drive Mobile Robot (DDMR), are numerically simulated, and the proposed SMHOESO is compared to several alternative types, demonstrating a significant reduction in controller energy, increased control signal smoothness, and accurate tracking of the reference signal.en_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleDesign and Stability Analysis of Sliding Mode Controller for Non-Holonomic Differential Drive Mobile Robotsen_US
dc.title.alternativeDesign and Stability Analysis of Sliding Mode Controller for Non-Holonomic Differential Drive Mobile Robotsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber0en_US
dc.source.volume11en_US
dc.source.journalMachinesen_US
dc.source.issue4en_US
dc.identifier.doi10.3390/machines11040470
dc.identifier.cristin2148469
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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