{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T15:50:59Z","timestamp":1780415459953,"version":"3.54.1"},"reference-count":38,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T00:00:00Z","timestamp":1742515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This study presents the formulation and verification of a novel online adaptive reconfigurable learning control algorithm (RLCA) for improved longitudinal motion control and disturbance compensation in Unmanned Aerial Vehicles (UAVs). The proposed algorithm is formulated to track the optimal trajectory yielded by the baseline Linear Quadratic Integral (LQI) controller. However, it also leverages reconfigurable dissipative and anti-dissipative actions to enhance adaptability under varying system dynamics. The anti-dissipative actor delivers an aggressive control effort to compensate for large errors, while the dissipative actor minimizes control energy expenditure under low error conditions to improve the control economy. The dissipative and anti-dissipative actors are augmented with state-error-driven hyperbolic scaling functions, which autonomously reconfigure the associated learning gains to mitigate disturbances and uncertainties, ensuring superior performance metrics such as tracking precision and disturbance rejection. By integrating the reconfigurable dissipative and anti-dissipative actions in its formulation, the proposed RLCA adaptively steers the control trajectory as the state conditions vary. The enhanced performance of the proposed RLCA in controlling the longitudinal motion of a small UAV model is validated via customized MATLAB simulations. The simulation results demonstrate the proposed control algorithm\u2019s efficacy in achieving rapid error convergence, disturbance rejection, and seamless adaptation to dynamic variations, as compared to the baseline LQI controller.<\/jats:p>","DOI":"10.3390\/a18040180","type":"journal-article","created":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T06:21:38Z","timestamp":1742797298000},"page":"180","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Adaptive Reconfigurable Learning Algorithm for Robust Optimal Longitudinal Motion Control of Unmanned Aerial Vehicles"],"prefix":"10.3390","volume":"18","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"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2739-1367","authenticated-orcid":false,"given":"Aliha","family":"Tanveer","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":[[2025,3,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Irfan, S., Zhao, L., Ullah, S., Javaid, U., and Iqbal, J. (2024). Differentiator- and observer-based feedback linearized advanced nonlinear control strategies for an unmanned aerial vehicle system. Drones, 8.","DOI":"10.3390\/drones8100527"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"104342","DOI":"10.1016\/j.robot.2022.104342","article-title":"A Review of quadrotor UAV: Control and SLAM methodologies ranging from conventional to innovative approaches","volume":"161","year":"2023","journal-title":"Robot. Auton. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"109633","DOI":"10.1016\/j.petrol.2021.109633","article-title":"UAV-based remote sensing for the petroleum industry and environmental monitoring: State-of-the-art and perspectives","volume":"208","author":"Asadzadeh","year":"2022","journal-title":"J. Petroleum Sci. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Li, H., Wang, C., Yuan, S., Zhu, H., Li, B., Liu, Y., and Sun, L. (2025). Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm. Algorithms, 18.","DOI":"10.3390\/a18020080"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"9069","DOI":"10.1109\/TITS.2024.3367769","article-title":"Minimum distance and minimum time optimal path planning with bioinspired machine learning algorithms for impaired unmanned air vehicles","volume":"25","author":"Tutsoy","year":"2024","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2810","DOI":"10.2514\/1.G001958","article-title":"Disturbance Rejection Flight Control for Small Fixed-Wing Unmanned Aerial Vehicles","volume":"39","author":"Liu","year":"2016","journal-title":"J. Guid. Control Dyn."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ducard, G., and Carughi, G. (2024). Neural Network Design and Training for Longitudinal Flight Control of a Tilt-Rotor Hybrid Vertical Takeoff and Landing Unmanned Aerial Vehicle. Drones, 8.","DOI":"10.3390\/drones8120727"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Yang, Y., Kim, S., Lee, K., and Leeghim, H. (2024). Disturbance Robust Attitude Stabilization of Multirotors with Control Moment Gyros. Sensors, 24.","DOI":"10.3390\/s24248212"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Bianchi, D., Di Gennaro, S., Di Ferdinando, M., and Acosta L\u00f9a, C. (2023). Robust Control of UAV with Disturbances and Uncertainty Estimation. Machines, 11.","DOI":"10.3390\/machines11030352"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1260\/1756-8293.7.2.203","article-title":"Enhanced Longitudinal Motion Control of UAV Simulation by Using P-LQR Method","volume":"7","author":"Yit","year":"2015","journal-title":"Int. J. Micro Air Vehicle"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Li, J., Liu, X., Wu, D., Pi, Z., and Liu, T. (2024). A High Performance Nonlinear Longitudinal Controller for Fixed-Wing UAVs Based on Fuzzy-Guaranteed Cost Control. Drones, 8.","DOI":"10.3390\/drones8110661"},{"key":"ref_12","first-page":"1313","article-title":"Investigation on PID controller usage on Unmanned Aerial Vehicle for stability control","volume":"66","author":"Yeshwant","year":"2022","journal-title":"Mater. Today: Proc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1007\/s11071-021-06341-2","article-title":"Identifying limits of linear control design validity in nonlinear systems: A continuation-based approach","volume":"104","author":"Nguyen","year":"2021","journal-title":"Nonlinear Dyn."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"10629","DOI":"10.1007\/s00500-019-04568-1","article-title":"Online adaptive PID tracking control of an aero-pendulum using PSO-scaled fuzzy gain adjustment mechanism","volume":"24","author":"Saleem","year":"2020","journal-title":"Soft Comput."},{"key":"ref_15","first-page":"132456","article-title":"A Fast-Convergent Hyperbolic Tangent PSO Algorithm for UAVs","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_16","first-page":"215","article-title":"Parameter Adaptation-Based Ant Colony Optimization with Dynamic Hybrid Mechanism","volume":"19","author":"Wang","year":"2020","journal-title":"Int. J. Comput. Intell. Appl."},{"key":"ref_17","first-page":"635","article-title":"Application of Hybrid Algorithm Based on Ant Colony Optimization and Particle Swarm Optimization in UAV Path Planning","volume":"101","author":"Zhang","year":"2023","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.neucom.2021.01.096","article-title":"dentification and optimal control of nonlinear systems using recurrent neural networks and reinforcement learning: An overview","volume":"438","author":"Yu","year":"2021","journal-title":"Neurocomput"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"4337","DOI":"10.1109\/TCSI.2021.3098830","article-title":"Adaptive Fuzzy Fast Finite-Time Dynamic Surface Tracking Control for Nonlinear Systems","volume":"68","author":"Wang","year":"2021","journal-title":"IEEE Trans. Circuit Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Moali, O., Mezghani, D., Mami, A., Oussar, A., and Nemra, A. (2024). UAV Trajectory Tracking Using Proportional-Integral-Derivative-Type-2 Fuzzy Logic Controller with Genetic Algorithm Parameter Tuning. Sensors, 24.","DOI":"10.3390\/s24206678"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Kuang, J., and Chen, M. (2024). Adaptive Sliding Mode Control for Trajectory Tracking of Quadrotor Unmanned Aerial Vehicles Under Input Saturation and Disturbances. Drones, 8.","DOI":"10.20944\/preprints202409.1088.v1"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"39239","DOI":"10.1016\/j.ijhydene.2022.09.083","article-title":"Double-layer fuzzy adaptive NMPC coordinated control method of energy management and trajectory tracking for hybrid electric fixed wing UAVs","volume":"47","author":"Tian","year":"2022","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"123428","DOI":"10.1016\/j.eswa.2024.123428","article-title":"Metaheuristic-assisted complex H-infinity flight control tuning for the Hawkeye unmanned aerial vehicle: A comparative study","volume":"248","author":"Kanokmedhakul","year":"2024","journal-title":"Expert. Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yanez-Badillo, H., Beltran-Carbajal, F., Tapia-Olvera, R., Favela-Contreras, A., Sotelo, C., and Sotelo, D. (2021). Adaptive robust motion control of quadrotor systems using artificial neural networks and particle swarm optimization. Mathematics, 9.","DOI":"10.3390\/math9192367"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.isatra.2021.04.043","article-title":"Longitudinal modeling and control for the convertible unmanned aerial vehicle: Theory and experiments","volume":"122","author":"Flores","year":"2022","journal-title":"ISA Trans."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Madeiras, J., Cardeira, C., Oliveira, P., Batista, P., and Silvestre, C. (2024). Saturated Trajectory Tracking Controller in the Body-Frame for Quadrotors. Drones, 8.","DOI":"10.3390\/drones8040163"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1109\/LCSYS.2018.2849576","article-title":"A Scalable Model-Based Learning Algorithm with Application to UAVs","volume":"2","author":"Liang","year":"2018","journal-title":"IEEE Control Syst. Lett."},{"key":"ref_28","first-page":"309","article-title":"Implementation of flight control system based on Kalman and PID controller for UAV","volume":"3","author":"Lwin","year":"2014","journal-title":"Int. J. Sci. Technol. Res."},{"key":"ref_29","first-page":"651","article-title":"Designing and simulation for vertical moving control of UAV system using PID, LQR and Fuzzy Logic","volume":"3","author":"Rahimi","year":"2013","journal-title":"Int. J. Elect. Comput. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"91367","DOI":"10.1109\/ACCESS.2019.2927000","article-title":"Robust H\u221e\/S-plane Controller of Longitudinal Control for UAVs","volume":"7","author":"Zhao","year":"2019","journal-title":"IEEE Access"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1108\/00022661011092938","article-title":"Longitudinal flight dynamic analysis of an agile UAV","volume":"82","author":"Maqsood","year":"2010","journal-title":"Aircr. Eng. Aerosp. Technol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Saleem, O., Kazim, M., and Iqbal, J. (2025). Robust Position Control of VTOL UAVs Using a Linear Quadratic Rate-Varying Integral Tracker: Design and Validation. Drones, 9.","DOI":"10.3390\/drones9010073"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Saleem, O., and Iqbal, J. (2024). Blood-glucose regulator design for diabetics based on LQIR-driven Sliding-Mode-Controller with self-adaptive reaching law. PLoS ONE, 19.","DOI":"10.1371\/journal.pone.0314479"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Lewis, F.L., Vrabie, D., and Syrmos, V.L. (2012). Optimal Control, John Wiley & Sons. [3rd ed.].","DOI":"10.1002\/9781118122631"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Saleem, O., Iqbal, J., and Afzal, M.S. (2023). A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights. PLoS ONE, 18.","DOI":"10.1371\/journal.pone.0283079"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"93185","DOI":"10.1109\/ACCESS.2024.3415494","article-title":"Phase-Based Adaptive Fractional LQR for Inverted-Pendulum-Type Robots: Formulation and Verification","volume":"12","author":"Saleem","year":"2024","journal-title":"IEEE Access"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1177\/0142331214527476","article-title":"An experimental investigation for error-cube PID control","volume":"37","author":"Alagoz","year":"2015","journal-title":"Trans. Inst. Meas. Control"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Hassan, M.A., Cao, Z., and Man, Z. (2023). Hyperbolic-Secant-Function-Based Fast Sliding Mode Control for Pantograph Robots. Machines, 11.","DOI":"10.3390\/machines11100941"}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/18\/4\/180\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:58:12Z","timestamp":1760029092000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/18\/4\/180"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,21]]},"references-count":38,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["a18040180"],"URL":"https:\/\/doi.org\/10.3390\/a18040180","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,21]]}}}