Transition control of a tail-sitter unmanned aerial vehicle with L1 neural network adaptive control

Zhong, Jingyang; WANG, Chen; ZHANG, Hang

doi:10.1016/j.cja.2023.04.002

Cited by 8 publications

(1 citation statement)

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“…Then, the controller performed the control adjustments using incremental nonlinear dynamic inversion (INDI) [11]. Next, Zhong et al [12] formulated a control system for a miniature tail-sitter vehicle during the transition phase using an L1 neural network adaptive control structure associated with PID control, which enhanced the compensation function and ensured a safe transition. Afterwards, Yang et al [13] developed a discrete-time linear quadratic regulator (LQR) with an initial deteriorate measure to identify the optimal system pole position, along with a novel angular acceleration estimation method utilized for compensating the unmodelled features.…”

Section: Introductionmentioning

confidence: 99%

Design of an Optimized Robust Deadbeat Controller for Roll Motion in Tail-Sitter VTOL UAVs

Mhmood

2024

JISC

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Unmanned Aerial Vehicles (UAVs), have recently sparked attention due to its versatility in a wide range of real-life uses. They require to be controlled so as to conduct different operations and widen their typical roles. This study proposes an optimal robust deadbeat controller for the roll angle motion of tail-sitter vertically take-off and land vehicles, taking into consideration the systems' intrinsic sensitivity to outside influences and fluctuation of their dynamics. Primarily, several assumptions are used to develop an appropriate transfer function that reflects the system physical attributes. The suggested controller is then formed in two sections: the first section addresses the nominal system's unstable dynamics, and the second element imposes the desired deadbeat performance and robustness. The control system variables are optimized using the creative and efficient Incomprehensible but Time-Intelligible Logics optimization technique, ensuring that the specified robustness demand is satisfied correctly. Finally, simulation is used to evaluate the developed controller effectiveness, revealing beneficial stability and performance indicators for both nominal and uncertain regulated system featuring uniform, bounded, and feasible closed-loop outputs. The control unit performs well, with a rising time of 0.0965 seconds, a settling time of 0.1134 seconds, and an overshoot of 0.167%.

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Section: Introductionmentioning

confidence: 99%