Hybrid method of adaptive control of variable mode of unmanned aerial vehicles with intelligent online compensation of disturbances
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Дата
2026
Автори
Назва журналу
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Видавець
Хмельницький національний університет
Анотація
The article resolves the current scientific and technical
contradiction between the need to increase the accuracy of navigation
control of autonomous unmanned aerial vehicles (UAVs) and the strict
resource constraints of on-board computing systems. An intelligent-robust
control architecture is proposed, based on the synthesis of the adaptive
alternating mode method (ASMC) and the recurrent neuro-fuzzy network
RSEFNN. The scientific novelty of the work lies in the improvement of the
hybrid approach, which, unlike classical robust methods, uses an intelligent
observer for online identification and compensation of nonlinear
components of dynamics and external disturbances. This made it possible
to significantly reduce the gain coefficients of the discontinuous part of the
controller, minimize the "rattling" effect, and increase the energy efficiency
of actuators. Mathematical proof of the stability of the closed-loop system
using the direct Lyapunov method confirmed the asymptotic convergence
of trajectory tracking errors to zero and guaranteed the numerical stability
of the neural network training processes. An important practical
contribution is the implementation of methods for suppressing highfrequency oscillations by replacing the discontinuous control function with
its smooth approximation based on the adaptive boundary layer and
hyperbolic tangent. To ensure the determinism of the computational cycle
in real time, optimization using the Padé method was applied, which
allowed minimizing algorithmic latency and achieving a control frequency
of up to 1000 Hz on embedded CPUs without specialized accelerators. The
results of the comparative analysis confirmed the high robustness of the
developed method under conditions of intense wind loads. In particular,
the use of the ASMC+RSEFNN controller allowed to increase the positioning
accuracy in steady state by 10.2–12.6 times compared to classical PID
controllers. The integrated neuro-fuzzy identifier provided effective
compensation for systematic wind shear, which is a critical factor for
performing UAV precision guidance tasks in difficult meteorological
conditions
Опис
Ключові слова
autonomous unmanned aerial vehicles (UAVs), adaptive switching mode control (ASMC), recurrent neural fuzzy network (RSEFNN), control system robustness, precision homing, online disturbance identification, Lyapunov method, chattering effect, embedded real-time systems, SWaP constraints, algorithmic latency, Padé method, control invariance, multisensor data fusion
Бібліографічний опис
Tanasiichuk S. Hybrid method of adaptive control of variable mode of unmanned aerial vehicles with intelligent online compensation of disturbances // Computer Systems and Information Technologies. 2026. No. 1. P. 205-214.