الملخص
تقدم هذه الورقة خوارزمية تحكم جديدة مثالية ومتينة قائمة على متحكم التكامل النسبي (PI) ووحدة التحكم في رد الفعل الراجع (SFB) مع مراقب اضطراب الحالة لنظام طائرات هليكوبتر تتحرك بدرجتين من الحرية. بدلا من استخدام الكسب العالي لرفض الاضطراب الخارجي، تم استخدام مراقب الاضطراب لتحسين متانة وحدة التحكم المقترحة. في حين تم تحسين أداء النظام المتحكم به من خلال الجمع بين وحدة التحكم PI ووحدة التحكم في ردود الفعل الخاصة بالحالة. من أجل التحقق من أداء ومتانة طريقة التحكم المقترحة، تم اجراء عمليات محاكاة تعتمد على Matlab 2022 لمقارنة وحدة التحكم المقترحة مع وحدة التحكم LQR. تمت المقارنة بين المتحكمات في ثلاث حالات: 1) النموذج الاسمي 2) رفض الاضطراب 3) عدم يقين النظام. تظهر الخوارزمية المقترحة خصائص جيدة بالقرب من تردد القطع، والتي يمكن تأكيدها بوضوح من خلال نتائج المجال الزمني.
المراجع
H. Liu, “Trajectory tracking control for a quadrotor helicopter in the presence of cyber-attacks,” ISA Trans., vol. 143, pp. 1–9, Dec. 2023.
B. Wang, X. Yu, L. Mu, and Y. Zhang, “Disturbance observer-based adaptive fault-tolerant control for a quadrotor helicopter subject to parametric uncertainties and external disturbances,” Mech. Syst. Signal Process., vol. 120, pp. 727–743, Apr. 2019.
H. Mary, A. H. Miry, and M. H. Miry, “Design robust H ∞ -PID controller for a helicopter system using sequential quadratic programming algorithm,” J. Chinese Inst. Eng., vol. 45, no. 8, pp. 688–696, Nov. 2022.
P. Nuthi and K. Subbarao, “Experimental Verification of Linear and Adaptive Control Techniques for a Two Degrees-of-Freedom Helicopter,” J. Dyn. Syst. Meas. Control, vol. 137, no. 6, Jun. 2015.
R. Ganapathy Subramanian and V. K. Elumalai, “Robust MRAC augmented baseline LQR for tracking control of 2 DoF helicopter,” Rob. Auton. Syst., vol. 86, pp. 70–77, Dec. 2016.
S. Karthick, S. Kanthalakshmi, E. Vinodh Kumar, V. Joshi Kumar, and A. Ezhil Kumaran, “Experimental Validation of Adaptive Augmented LQI Control for a 2 DoF Helicopter,” IETE J. Res., pp. 1–13, Nov. 2022.
T. KARA and A. H. MARY, “Adaptive PD-SMC for Nonlinear Robotic Manipulator Tracking Control,” Stud. Informatics Control, vol. 26, no. 1, Mar. 2017.
K. R. Palepogu and S. Mahapatra, “Design of sliding mode control with state varying gains for a Benchmark Twin Rotor MIMO System in Horizontal Motion,” Eur. J. Control, p. 100909, Oct. 2023.
T. Jiang, D. Lin, and T. Song, “Novel integral sliding mode control for small-scale unmanned helicopters,” J. Franklin Inst., vol. 356, no. 5, pp. 2668–2689, Mar. 2019.
W. Boukadida, A. Benamor, H. Messaoud, and P. Siarry, “Multi-objective design of optimal higher order sliding mode control for robust tracking of 2-DoF helicopter system based on metaheuristics,” Aerosp. Sci. Technol., vol. 91, pp. 442–455, Aug. 2019.
S. M. Schlanbusch and J. Zhou, “Adaptive predictor-based control for a helicopter system with input delays: Design and experiments,” J. Autom. Intell., Feb. 2024.
F. Chen, R. Jiang, C. Wen, and R. Su, “Self-repairing control of a helicopter with input time delay via adaptive global sliding mode control and quantum logic,” Inf. Sci. (Ny)., vol. 316, pp. 123–131, Sep. 2015.
Y. Zhu and H. Zhao, “Robust control design for Electric Helicopter Tail Deceleration system: Fuzzy view and Stackelberg game theory-based optimization,” ISA Trans., vol. 145, pp. 51–62, Feb. 2024.
M. Raghappriya and S. Kanthalakshmi, “Particle filter-based adaptive super-twisting sliding mode fault-tolerant control for helicopter systems,” Int. J. Dyn. Control, Nov. 2023.
T. A. Mahmoud, M. El-Hossainy, B. Abo-Zalam, and R. Shalaby, “Fractional-order fuzzy sliding mode control of uncertain nonlinear MIMO systems using fractional-order reinforcement learning,” Complex Intell. Syst., Jan. 2024.
A. H. Mary, T. Kara, and A. H. Miry, “Inverse kinematics solution for robotic manipulators based on fuzzy logic and PD control,” in 2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA), May 2016, pp. 1–6.
M. M. A. Al-Isawi, A. J. Attiya, and J. O. ADOGHE, “UAV Control Based on Dual LQR and Fuzzy-PID Controller,” Al-Khwarizmi Eng. J., vol. 16, no. 3, pp. 43–53, Sep. 2020.
S. Naderi, M. J. Blondin, and B. Rezaie, “Optimizing an adaptive fuzzy logic controller of a 3-DOF helicopter with a modified PSO algorithm,” Int. J. Dyn. Control, vol. 11, no. 4, pp. 1895–1913, Aug. 2023.
Y. Hu, Y. Yang, S. Li, and Y. Zhou, “Fuzzy controller design of micro-unmanned helicopter relying on improved genetic optimization algorithm,” Aerosp. Sci. Technol., vol. 98, p. 105685, Mar. 2020.
F. Pakro and A. A. Nikkhah, “A fuzzy adaptive controller design for integrated guidance and control of a nonlinear model helicopter,” Int. J. Dyn. Control, vol. 11, no. 2, pp. 701–716, Apr. 2023.
M. S. Ahmed, A. H. M. Mary, and H. H. Jasim, “Robust Computed Torque Control for Uncertain Robotic Manipulators,” Al-Khwarizmi Eng. J., vol. 17, no. 3, pp. 22–28, Sep. 2021.
F. Gopmandal and A. Ghosh, “LQR-based MIMO PID control of a 2-DOF helicopter system with uncertain cross-coupled gain,” IFAC-PapersOnLine, vol. 55, no. 22, pp. 183–188, 2022.
R. Shalaby, M. El-Hossainy, B. Abo-Zalam, and T. A. Mahmoud, “Optimal fractional-order PID controller based on fractional-order actor-critic algorithm,” Neural Comput. Appl., vol. 35, no. 3, pp. 2347–2380, Jan. 2023.
S. S. Butt, H. Sun, and H. Aschemann, “Comparison of Backstepping-Based Sliding Mode and Adaptive Backstepping for a Robust Control of a Twin Rotor Helicopter,” 2016, pp. 3–30.
L. A. Ramírez, M. A. Zuñiga, G. Romero, E. Alcorta-García, and A. J. Muñoz-Vázquez, “Fault Diagnosis for a Class of Robotic Systems with Application to 2-DOF Helicopter,” Appl. Sci., vol. 10, no. 23, p. 8359, Nov. 2020.
هذا العمل مرخص بموجب Creative Commons Attribution 4.0 International License.
الحقوق الفكرية (c) 2024 مجلة الخوارزمي الهندسية