Identification and adaptive PID Control of a hexacopter UAV based on neural networks

DOI10.1002/ACS.2955zbMath1407.93177OpenAlexW2901945359WikidataQ128818491 ScholiaQ128818491MaRDI QIDQ4625249

Carlos Soria, Claudio D. Rosales, Francisco Guido Rossomando

Publication date: 22 February 2019

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.2955

zbMATH Keywords

identificationneural networksadaptive PIDdiscrete stability analysishexacopter

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Control/observation systems governed by partial differential equations (93C20) Neural networks for/in biological studies, artificial life and related topics (92B20) Adaptive control/observation systems (93C40) Lyapunov and other classical stabilities (Lagrange, Poisson, (L^p, l^p), etc.) in control theory (93D05) Automated systems (robots, etc.) in control theory (93C85)

Related Items (3)

Fault‐tolerant attitude tracking control with practical finite time convergence for unmanned aerial vehicles under actuation faults ⋮ Trajectory tracking double two-loop adaptive neural network control for a quadrotor ⋮ Adaptive finite‐time tracking control for output‐constrained nonlinear systems with non‐strict‐feedback structure

Uses Software

• DroneKit Python

Cites Work

• Unnamed Item
• Accurate modeling and robust hovering control for a quad-rotor VTOL aircraft
• Discrete-time high order neural control. Trained with Kalman filtering
• Approximate H∞ loop shaping in PID parameter adaptation
• Adaptive backstepping flight control for a mini‐UAV

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