Optimizing flight path accuracy of an autonomous quadrotor in windy conditions: integrated control strategies for tracking under perturbations and uncertainties

• Published in: International journal of dynamics and control 2024-11, Vol.12 (11), p.4120-4137
• Main Authors: Abdelmaksoud, Sherif I., Mailah, Musa
• Format: Article
• Language: English
• Subjects: Accuracy; Adaptive control; Adaptive systems; Algorithms; Artificial neural networks; Complexity; Control; Control and Systems Theory; Control methods; Control stability; Disturbances; Dynamical Systems; Effectiveness; Engineering; Fuzzy control; Fuzzy logic; Gusts; Machine learning; Nonlinear control; Nonlinear systems; Parameter estimation; Perturbation; Proportional integral derivative; Rotary wing aircraft; Systems stability; Tracking; Turbulence models; Uncertainty; Unmanned aerial vehicles; Vibration; Wind effects
• ISSN: 2195-268X; 2195-2698
• DOI: 10.1007/s40435-024-01487-4

Challenges and unpredictability pose significant barriers to maintaining stable operation in rotorcraft unmanned aerial vehicle (UAV) systems. The quadrotor model, as a type of rotorcraft UAV, is currently recognized as an exceptionally adaptable flying machine, serving various purposes in both civilian and military domains. However, it is a complex and highly non-linear system, and its effectiveness may suffer when subjected to external disturbances or uncertainties in its design. Using a technique known as active force control (AFC), novel intelligent control methods for quadrotors were presented in this study in order to enhance their ability to reject disturbances and uncertainties while maintaining system stability. To achieve this, a designed PID controller and an AFC technique were combined in a hybrid way into a single control strategy. To automatically estimate control parameters, the iterative learning algorithm (ILA), artificial neural network, and Adaptive Neuro-Fuzzy Inference System (ANFIS) were utilized, and the proposed control schemes became known as the PID-ILAFC, PID-NNAFC, and PID-ANFISAFC. To assess the effectiveness and resilience of the proposed control approaches, various perturbation representatives, including sinusoid and Dryden turbulence models, were employed along with uncertainties. The performance of the suggested control methods was evaluated using integral square error. Findings reveal an average decrease of over 55% in settling time across most scenarios. Concerning trajectory tracking accuracy, the integrated control strategies demonstrated remarkable efficacy in following the intended paths of the quadrotor, effectively mitigating the effects of applied wind gusts and uncertainties.