{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T14:29:31Z","timestamp":1781620171361,"version":"3.54.5"},"reference-count":57,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>This paper presents the constitution of a computationally intelligent self-adaptive steering controller for a lawn-mowing robot to yield robust trajectory tracking and disturbance rejection behavior. The conventional fixed-gain proportional\u2013integral\u2013derivative (PID) control procedure lacks the flexibility to deal with the environmental indeterminacies, coupling issues, and intrinsic nonlinear dynamics associated with the aforementioned nonholonomic system. Hence, this article contributes to formulating a self-adaptive single-neuron PID control system that is driven by an extended Kalman filter (EKF) to ensure efficient learning and faster convergence speeds. The neural adaptive PID control formulation improves the controller\u2019s design flexibility, which allows it to effectively attenuate the tracking errors and improve the system\u2019s trajectory tracking accuracy. To supplement the controller\u2019s robustness to exogenous disturbances, the adaptive PID control signal is modulated with an auxiliary fuzzy-immune system. The fuzzy-immune system imitates the automatic self-learning and self-tuning characteristics of the biological immune system to suppress bounded disturbances and parametric variations. The propositions above are verified by performing the tailored hardware in the loop experiments on a differentially driven lawn-mowing robot. The results of these experiments confirm the enhanced trajectory tracking precision and disturbance compensation ability of the prescribed control method.<\/jats:p>","DOI":"10.3390\/computers13110301","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T04:53:05Z","timestamp":1731991985000},"page":"301","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A Fuzzy-Immune-Regulated Single-Neuron Proportional\u2013Integral\u2013Derivative Control System for Robust Trajectory Tracking in a Lawn-Mowing Robot"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2197-9302","authenticated-orcid":false,"given":"Omer","family":"Saleem","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, National University of Computer and Emerging Sciences, Lahore 54770, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmad","family":"Hamza","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National University of Computer and Emerging Sciences, Lahore 54770, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0795-0282","authenticated-orcid":false,"given":"Jamshed","family":"Iqbal","sequence":"additional","affiliation":[{"name":"School of Computer Science, Faculty of Science and Engineering, University of Hull, Hull HU6 7RX, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1108\/IR-04-2020-0082","article-title":"Comprehensive study of skid-steer wheeled mobile robots: Development and challenges","volume":"48","author":"Khan","year":"2021","journal-title":"Ind. 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