Neuro sliding mode control of quadrotor UAVs carrying suspended payload
Özhan Bingöl, H. M. Güzey
Abstract
In this paper, a neuro-sliding mode controller (SMC) has been designed for a quadrotor transporting a suspended payload. SMCs are very efficient under uncertain conditions. However, if the uncertain dynamics change over time, SMC gains need to be updated to maintain the tracking performance. This study proposes a neuro-SMC to control a quadrotor UAV carrying a suspended payload in the existence of time-varying uncertain dynamics. Once the accuracy of the proposed controller is demonstrated theoretically using the Lyapunov stability criterion, the effectiveness of the proposed controller is shown in simulation, which confirms the theoretical claims.
Topics & Concepts
Payload (computing)Control theory (sociology)Controller (irrigation)Lyapunov functionSliding mode controlLyapunov stabilityTracking (education)Control engineeringMode (computer interface)EngineeringComputer scienceControl (management)Nonlinear systemArtificial intelligencePhysicsBiologyOperating systemPedagogyPsychologyNetwork packetAgronomyQuantum mechanicsComputer networkAdaptive Control of Nonlinear SystemsDistributed Control Multi-Agent SystemsAdaptive Dynamic Programming Control